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Editors: Francisco Ruiz, Jennifer Dy, Jan-Willem van de Meent
Blessing of Class Diversity in Pre-training
; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:283-305
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BaCaDI: Bayesian Causal Discovery with Unknown Interventions
Alexander Hägele, Jonas Rothfuss, Lars Lorch, Vignesh Ram Somnath, Bernhard Schölkopf, Andreas Krause; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1411-1436
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Discovering Many Diverse Solutions with Bayesian Optimization
Natalie Maus, Kaiwen Wu, David Eriksson, Jacob Gardner; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1779-1798
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Multilevel Bayesian Quadrature
Kaiyu Li, Daniel Giles, Toni Karvonen, Serge Guillas, Francois-Xavier Briol; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1845-1868
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Distance-to-Set Priors and Constrained Bayesian Inference
Rick Presman, Jason Xu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2310-2326
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Error Estimation for Random Fourier Features
Junwen Yao, N. Benjamin Erichson, Miles E. Lopes; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2348-2364
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Noisy Low-rank Matrix Optimization: Geometry of Local Minima and Convergence Rate
Ziye Ma, Somayeh Sojoudi; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3125-3150
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Generalized PTR: User-Friendly Recipes for Data-Adaptive Algorithms with Differential Privacy
Rachel Redberg, Yuqing Zhu, Yu-Xiang Wang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3977-4005
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A Tale of Sampling and Estimation in Discounted Reinforcement Learning
Alberto Maria Metelli, Mirco Mutti, Marcello Restelli; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4575-4601
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An Efficient and Continuous Voronoi Density Estimator
Giovanni Luca Marchetti, Vladislav Polianskii, Anastasiia Varava, Florian T. Pokorny, Danica Kragic; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4732-4744
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Safe Sequential Testing and Effect Estimation in Stratified Count Data
Rosanne Turner, Peter Grunwald; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4880-4893
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Particle algorithms for maximum likelihood training of latent variable models
Juan Kuntz, Jen Ning Lim, Adam M. Johansen; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5134-5180
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Inducing Point Allocation for Sparse Gaussian Processes in High-Throughput Bayesian Optimisation
Henry B. Moss, Sebastian W. Ober, Victor Picheny; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5213-5230
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Implications of sparsity and high triangle density for graph representation learning
Hannah Sansford, Alexander Modell, Nick Whiteley, Patrick Rubin-Delanchy; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5449-5473
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The Schrödinger Bridge between Gaussian Measures has a Closed Form
Charlotte Bunne, Ya-Ping Hsieh, Marco Cuturi, Andreas Krause; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5802-5833
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Federated Learning under Distributed Concept Drift
Ellango Jothimurugesan, Kevin Hsieh, Jianyu Wang, Gauri Joshi, Phillip B. Gibbons; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5834-5853
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Data Banzhaf: A Robust Data Valuation Framework for Machine Learning
Jiachen T. Wang, Ruoxi Jia; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6388-6421
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Indeterminacy in Generative Models: Characterization and Strong Identifiability
Quanhan Xi, Benjamin Bloem-Reddy; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6912-6939
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Do Bayesian Neural Networks Need To Be Fully Stochastic?
Mrinank Sharma, Sebastian Farquhar, Eric Nalisnick, Tom Rainforth; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7694-7722
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Mode-Seeking Divergences: Theory and Applications to GANs
Cheuk Ting Li, Farzan Farnia; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8321-8350
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Fix-A-Step: Semi-supervised Learning From Uncurated Unlabeled Data
Zhe Huang, Mary-Joy Sidhom, Benjamin Wessler, Michael C. Hughes; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8373-8394
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Rethinking Initialization of the Sinkhorn Algorithm
James Thornton, Marco Cuturi; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8682-8698
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Don’t be fooled: label leakage in explanation methods and the importance of their quantitative evaluation
Neil Jethani, Adriel Saporta, Rajesh Ranganath; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8925-8953
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Origins of Low-Dimensional Adversarial Perturbations
Elvis Dohmatob, Chuan Guo, Morgane Goibert; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9221-9237
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Scalable Bicriteria Algorithms for Non-Monotone Submodular Cover
Victoria Crawford; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9517-9537
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Huber-robust confidence sequences
Hongjian Wang, Aaditya Ramdas; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9662-9679
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Hedging against Complexity: Distributionally Robust Optimization with Parametric Approximation
Garud Iyengar, Henry Lam, Tianyu Wang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9976-10011
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Who Should Predict? Exact Algorithms For Learning to Defer to Humans
Hussein Mozannar, Hunter Lang, Dennis Wei, Prasanna Sattigeri, Subhro Das, David Sontag; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10520-10545
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Implicit Graphon Neural Representation
Xinyue Xia, Gal Mishne, Yusu Wang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10619-10634
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Fitting low-rank models on egocentrically sampled partial networks
Ga Ming Angus Chan, Tianxi Li; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10635-10649
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The Power of Recursion in Graph Neural Networks for Counting Substructures
Behrooz Tahmasebi, Derek Lim, Stefanie Jegelka; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11023-11042
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Using Sliced Mutual Information to Study Memorization and Generalization in Deep Neural Networks
Shelvia Wongso, Rohan Ghosh, Mehul Motani; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11608-11629
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Improved Generalization Bound and Learning of Sparsity Patterns for Data-Driven Low-Rank Approximation
Shinsaku Sakaue, Taihei Oki; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1-10
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Meta-Uncertainty in Bayesian Model Comparison
Marvin Schmitt, Stefan T. Radev, Paul-Christian Bürkner; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11-29
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PAC Learning of Halfspaces with Malicious Noise in Nearly Linear Time
Jie Shen; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:30-46
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Entropic Risk Optimization in Discounted MDPs
Jia Lin Hau, Marek Petrik, Mohammad Ghavamzadeh; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:47-76
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Acceleration of Frank-Wolfe Algorithms with Open-Loop Step-Sizes
Elias Wirth, Thomas Kerdreux, Sebastian Pokutta; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:77-100
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An Online and Unified Algorithm for Projection Matrix Vector Multiplication with Application to Empirical Risk Minimization
Lianke Qin, Zhao Song, Lichen Zhang, Danyang Zhuo; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:101-156
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Leveraging Instance Features for Label Aggregation in Programmatic Weak Supervision
Jieyu Zhang, Linxin Song, Alex Ratner; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:157-171
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Stochastic Gradient Descent-Ascent: Unified Theory and New Efficient Methods
Aleksandr Beznosikov, Eduard Gorbunov, Hugo Berard, Nicolas Loizou; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:172-235
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Scalable marked point processes for exchangeable and non-exchangeable event sequences
Aristeidis Panos, Ioannis Kosmidis, Petros Dellaportas; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:236-252
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Bayesian Variable Selection in a Million Dimensions
Martin Jankowiak; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:253-282
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Barlow Graph Auto-Encoder for Unsupervised Network Embedding
Rayyan Ahmad Khan, Martin Kleinsteuber; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:306-322
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Gradient-Informed Neural Network Statistical Robustness Estimation
Karim TIT, Teddy Furon, Mathias Rousset; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:323-334
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Online Defense Strategies for Reinforcement Learning Against Adaptive Reward Poisoning
Andi Nika, Adish Singla, Goran Radanovic; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:335-358
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A Case of Exponential Convergence Rates for SVM
Vivien Cabannnes, Stefano Vigogna; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:359-374
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Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models via Reinforcement Learning
Ruitu Xu, Yifei Min, Tianhao Wang, Michael I. Jordan, Zhaoran Wang, Zhuoran Yang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:375-407
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Adaptive Cholesky Gaussian Processes
Simon Bartels, Kristoffer Stensbo-Smidt, Pablo Moreno-Munoz, Wouter Boomsma, Jes Frellsen, Soren Hauberg; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:408-452
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Sample Complexity of Kernel-Based Q-Learning
Sing-Yuan Yeh, Fu-Chieh Chang, Chang-Wei Yueh, Pei-Yuan Wu, Alberto Bernacchia, Sattar Vakili; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:453-469
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A principled framework for the design and analysis of token algorithms
Hadrien Hendrikx; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:470-489
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Learning k-qubit Quantum Operators via Pauli Decomposition
Mohsen Heidari, Wojciech Szpankowski; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:490-504
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Semi-Verified PAC Learning from the Crowd
Shiwei Zeng, Jie Shen; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:505-522
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On the Capacity Limits of Privileged ERM
Michal Sharoni, Sivan Sabato; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:523-534
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USIM Gate: UpSampling Module for Segmenting Precise Boundaries concerning Entropy
Kyungsu Lee, Haeyun Lee, Jae Youn Hwang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:535-562
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Bayesian Structure Scores for Probabilistic Circuits
Yang Yang, Gennaro Gala, Robert Peharz; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:563-575
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Langevin Diffusion Variational Inference
Tomas Geffner, Justin Domke; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:576-593
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Overcoming Prior Misspecification in Online Learning to Rank
Javad Azizi, Ofer Meshi, Masrour Zoghi, Maryam Karimzadehgan; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:594-614
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Catalyst Acceleration of Error Compensated Methods Leads to Better Communication Complexity
Xun Qian, Hanze Dong, Tong Zhang, Peter Richtarik; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:615-649
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Kernel Conditional Moment Constraints for Confounding Robust Inference
Kei Ishikawa, Niao He; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:650-674
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Meta-learning for Robust Anomaly Detection
Atsutoshi Kumagai, Tomoharu Iwata, Hiroshi Takahashi, Yasuhiro Fujiwara; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:675-691
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Learning in RKHM: a C*-Algebraic Twist for Kernel Machines
Yuka Hashimoto, Masahiro Ikeda, Hachem Kadri; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:692-708
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From Shapley Values to Generalized Additive Models and back
Sebastian Bordt, Ulrike von Luxburg; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:709-745
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Estimating Conditional Average Treatment Effects with Missing Treatment Information
Milan Kuzmanovic, Tobias Hatt, Stefan Feuerriegel; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:746-766
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Global Convergence of Over-parameterized Deep Equilibrium Models
Zenan Ling, Xingyu Xie, Qiuhao Wang, Zongpeng Zhang, Zhouchen Lin; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:767-787
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A Tale of Two Efficient Value Iteration Algorithms for Solving Linear MDPs with Large Action Space
Zhaozhuo Xu, Zhao Song, Anshumali Shrivastava; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:788-836
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Adversarial De-confounding in Individualised Treatment Effects Estimation
Vinod K. Chauhan, Soheila Molaei, Marzia Hoque Tania, Anshul Thakur, Tingting Zhu, David A. Clifton; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:837-849
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Fast Distributed k-Means with a Small Number of Rounds
Tom Hess, Ron Visbord, Sivan Sabato; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:850-874
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A New Causal Decomposition Paradigm towards Health Equity
Xinwei Sun, Xiangyu Zheng, Jim Weinstein; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:875-890
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Matching Map Recovery with an Unknown Number of Outliers
Arshak Minasyan, Tigran Galstyan, Sona Hunanyan, Arnak Dalalyan; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:891-906
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Characterizing Internal Evasion Attacks in Federated Learning
Taejin Kim, Shubhranshu Singh, Nikhil Madaan, Carlee Joe-Wong; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:907-921
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Optimal and Private Learning from Human Response Data
Duc Nguyen, Anderson Ye Zhang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:922-958
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Bayesian Optimization with Conformal Prediction Sets
Samuel Stanton, Wesley Maddox, Andrew Gordon Wilson; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:959-986
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Alternating Projected SGD for Equality-constrained Bilevel Optimization
Quan Xiao, Han Shen, Wotao Yin, Tianyi Chen; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:987-1023
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Improved Robust Algorithms for Learning with Discriminative Feature Feedback
Sivan Sabato; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1024-1036
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Weisfeiler and Leman go Hyperbolic: Learning Distance Preserving Node Representations
Giannis Nikolentzos, Michail Chatzianastasis, Michalis Vazirgiannis; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1037-1054
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Can 5th Generation Local Training Methods Support Client Sampling? Yes!
Michał Grudzień, Grigory Malinovsky, Peter Richtarik; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1055-1092
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qEUBO: A Decision-Theoretic Acquisition Function for Preferential Bayesian Optimization
Raul Astudillo, Zhiyuan Jerry Lin, Eytan Bakshy, Peter Frazier; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1093-1114
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Bayesian Hierarchical Models for Counterfactual Estimation
Natraj Raman, Daniele Magazzeni, Sameena Shah; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1115-1128
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Sequential Gradient Descent and Quasi-Newton’s Method for Change-Point Analysis
Xianyang Zhang, Trisha Dawn; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1129-1143
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Towards Scalable and Robust Structured Bandits: A Meta-Learning Framework
Runzhe Wan, Lin Ge, Rui Song; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1144-1173
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Compress Then Test: Powerful Kernel Testing in Near-linear Time
Carles Domingo-Enrich, Raaz Dwivedi, Lester Mackey; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1174-1218
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Select and Optimize: Learning to solve large-scale TSP instances
Hanni Cheng, Haosi Zheng, Ya Cong, Weihao Jiang, Shiliang Pu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1219-1231
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Fixing by Mixing: A Recipe for Optimal Byzantine ML under Heterogeneity
Youssef Allouah, Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, John Stephan; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1232-1300
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Testing of Horn Samplers
Ansuman Banerjee, Shayak Chakraborty, Sourav Chakraborty, Kuldeep S. Meel, Uddalok Sarkar, Sayantan Sen; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1301-1330
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Coordinate Ascent for Off-Policy RL with Global Convergence Guarantees
Hsin-En Su, Yen-Ju Chen, Ping-Chun Hsieh, Xi Liu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1331-1378
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Positional Encoder Graph Neural Networks for Geographic Data
Konstantin Klemmer, Nathan S. Safir, Daniel B. Neill; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1379-1389
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Coarse-Grained Smoothness for Reinforcement Learning in Metric Spaces
Omer Gottesman, Kavosh Asadi, Cameron S. Allen, Samuel Lobel, George Konidaris, Michael Littman; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1390-1410
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Statistical Analysis of Karcher Means for Random Restricted PSD Matrices
Hengchao Chen, Xiang Li, Qiang Sun; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1437-1456
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Differentially Private Synthetic Control
Saeyoung Rho, Rachel Cummings, Vishal Misra; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1457-1491
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Scalable Bayesian Optimization Using Vecchia Approximations of Gaussian Processes
Felix Jimenez, Matthias Katzfuss; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1492-1512
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On the Neural Tangent Kernel Analysis of Randomly Pruned Neural Networks
Hongru Yang, Zhangyang Wang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1513-1553
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Riemannian Accelerated Gradient Methods via Extrapolation
Andi Han, Bamdev Mishra, Pratik Jawanpuria, Junbin Gao; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1554-1585
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Flexible risk design using bi-directional dispersion
Matthew J. Holland; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1586-1623
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Contextual Linear Bandits under Noisy Features: Towards Bayesian Oracles
Jung-Hun Kim, Se-Young Yun, Minchan Jeong, Junhyun Nam, Jinwoo Shin, Richard Combes; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1624-1645
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Deep equilibrium models as estimators for continuous latent variables
Russell Tsuchida, Cheng Soon Ong; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1646-1671
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Refined Convergence and Topology Learning for Decentralized SGD with Heterogeneous Data
Batiste Le Bars, Aurélien Bellet, Marc Tommasi, Erick Lavoie, Anne-Marie Kermarrec; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1672-1702
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A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces
Charline Le Lan, Joshua Greaves, Jesse Farebrother, Mark Rowland, Fabian Pedregosa, Rishabh Agarwal, Marc G. Bellemare; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1703-1718
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A Constant-Factor Approximation Algorithm for Reconciliation $k$-Median
Joachim Spoerhase, Kamyar Khodamoradi, Benedikt Riegel, Bruno Ordozgoiti, Aristides Gionis; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1719-1746
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Neural Laplace Control for Continuous-time Delayed Systems
Samuel Holt, Alihan Hüyük, Zhaozhi Qian, Hao Sun, Mihaela van der Schaar; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1747-1778
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BlitzMask: Real-Time Instance Segmentation Approach for Mobile Devices
Vitalii Bulygin, Dmytro Mykheievskyi, Kyrylo Kuchynskyi; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1799-1811
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Exact Gradient Computation for Spiking Neural Networks via Forward Propagation
Jane H. Lee, Saeid Haghighatshoar, Amin Karbasi; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1812-1831
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Uni6Dv2: Noise Elimination for 6D Pose Estimation
Mingshan Sun, Ye Zheng, Tianpeng Bao, Jianqiu Chen, Guoqiang Jin, Liwei Wu, Rui Zhao, Xiaoke Jiang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1832-1844
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Direct Inference of Effect of Treatment (DIET) for a Cookieless World
Shiv Shankar, Ritwik Sinha, Saayan Mitra, Moumita Sinha, Madalina Fiterau; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1869-1887
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The Ordered Matrix Dirichlet for State-Space Models
Niklas Stoehr, Benjamin J. Radford, Ryan Cotterell, Aaron Schein; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1888-1903
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Energy-Based Models for Functional Data using Path Measure Tilting
Jen Ning Lim, Sebastian Vollmer, Lorenz Wolf, Andrew Duncan; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1904-1923
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Frequentist Uncertainty Quantification in Semi-Structured Neural Networks
Emilio Dorigatti, Benjamin Schubert, Bernd Bischl, David Ruegamer; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1924-1941
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NTS-NOTEARS: Learning Nonparametric DBNs With Prior Knowledge
Xiangyu Sun, Oliver Schulte, Guiliang Liu, Pascal Poupart; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1942-1964
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One Policy is Enough: Parallel Exploration with a Single Policy is Near-Optimal for Reward-Free Reinforcement Learning
Pedro Cisneros-Velarde, Boxiang Lyu, Sanmi Koyejo, Mladen Kolar; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:1965-2001
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Variational Inference for Neyman-Scott Processes
Chengkuan Hong, Christian Shelton; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2002-2018
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Graph Alignment Kernels using Weisfeiler and Leman Hierarchies
Giannis Nikolentzos, Michalis Vazirgiannis; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2019-2034
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Geometric Random Walk Graph Neural Networks via Implicit Layers
Giannis Nikolentzos, Michalis Vazirgiannis; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2035-2053
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Model-X Sequential Testing for Conditional Independence via Testing by Betting
Shalev Shaer, Gal Maman, Yaniv Romano; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2054-2086
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Mixed-Effect Thompson Sampling
Imad Aouali, Branislav Kveton, Sumeet Katariya; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2087-2115
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Mixed Linear Regression via Approximate Message Passing
Nelvin Tan, Ramji Venkataramanan; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2116-2131
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EEGNN: Edge Enhanced Graph Neural Network with a Bayesian Nonparametric Graph Model
Yirui Liu, Xinghao Qiao, Liying Wang, Jessica Lam; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2132-2146
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Estimating Total Correlation with Mutual Information Estimators
Ke Bai, Pengyu Cheng, Weituo Hao, Ricardo Henao, Larry Carin; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2147-2164
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Vector Optimization with Stochastic Bandit Feedback
Cagin Ararat, Cem Tekin; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2165-2190
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Knowledge Acquisition for Human-In-The-Loop Image Captioning
Ervine Zheng, Qi Yu, Rui Li, Pengcheng Shi, Anne Haake; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2191-2206
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A Statistical Analysis of Polyak-Ruppert Averaged Q-Learning
Xiang Li, Wenhao Yang, Jiadong Liang, Zhihua Zhang, Michael I. Jordan; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2207-2261
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Linear Convergence of Gradient Descent For Finite Width Over-parametrized Linear Networks With General Initialization
Ziqing Xu, Hancheng Min, Salma Tarmoun, Enrique Mallada, Rene Vidal; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2262-2284
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“Plus/minus the learning rate”: Easy and Scalable Statistical Inference with SGD
Jerry Chee, Hwanwoo Kim, Panos Toulis; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2285-2309
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Fast Computation of Branching Process Transition Probabilities via ADMM
Achal Awasthi, Jason Xu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2327-2347
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AdaGDA: Faster Adaptive Gradient Descent Ascent Methods for Minimax Optimization
Feihu Huang, Xidong Wu, Zhengmian Hu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2365-2389
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Classification of Adolescents’ Risky Behavior in Instant Messaging Conversations
Jaromı́r Plhák, Ondřej Sotolář, Michaela Lebedı́ková, David Šmahel; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2390-2404
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Robust Linear Regression for General Feature Distribution
Tom Norman, Nir Weinberger, Kfir Y. Levy; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2405-2435
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Fair learning with Wasserstein barycenters for non-decomposable performance measures
Solenne Gaucher, Nicolas Schreuder, Evgenii Chzhen; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2436-2459
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Deep Neural Networks with Efficient Guaranteed Invariances
Matthias Rath, Alexandru Paul Condurache; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2460-2480
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Fast Block Coordinate Descent for Non-Convex Group Regularizations
Yasutoshi Ida, Sekitoshi Kanai, Atsutoshi Kumagai; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2481-2493
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AUC-based Selective Classification
Andrea Pugnana, Salvatore Ruggieri; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2494-2514
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Nonparametric Indirect Active Learning
Shashank Singh; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2515-2541
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Resolving the Approximability of Offline and Online Non-monotone DR-Submodular Maximization over General Convex Sets
Loay Mualem, Moran Feldman; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2542-2564
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{PF}$^2$ES: Parallel Feasible Pareto Frontier Entropy Search for Multi-Objective Bayesian Optimization
Jixiang Qing, Henry B. Moss, Tom Dhaene, Ivo Couckuyt; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2565-2588
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Learning Constrained Structured Spaces with Application to Multi-Graph Matching
Hedda Cohen Indelman, Tamir Hazan; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2589-2602
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On the Strategyproofness of the Geometric Median
El-Mahdi El-Mhamdi, Sadegh Farhadkhani, Rachid Guerraoui, Lê-Nguyên Hoang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2603-2640
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Covariate-informed Representation Learning to Prevent Posterior Collapse of iVAE
Young-Geun Kim, Ying Liu, Xue-Xin Wei; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2641-2660
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EGG-GAE: scalable graph neural networks for tabular data imputation
Lev Telyatnikov, Simone Scardapane; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2661-2676
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Group Distributionally Robust Reinforcement Learning with Hierarchical Latent Variables
Mengdi Xu, Peide Huang, Yaru Niu, Visak Kumar, Jielin Qiu, Chao Fang, Kuan-Hui Lee, Xuewei Qi, Henry Lam, Bo Li, Ding Zhao; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2677-2703
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Weather2K: A Multivariate Spatio-Temporal Benchmark Dataset for Meteorological Forecasting Based on Real-Time Observation Data from Ground Weather Stations
Xun Zhu, Yutong Xiong, Ming Wu, Gaozhen Nie, Bin Zhang, Ziheng Yang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2704-2722
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Improved Rate of First Order Algorithms for Entropic Optimal Transport
Yiling Luo, Yiling Xie, Xiaoming Huo; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2723-2750
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Conformal Off-Policy Prediction
Yingying Zhang, Chengchun Shi, Shikai Luo; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2751-2768
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Sparse Spectral Bayesian Permanental Process with Generalized Kernel
Jeremy Sellier, Petros Dellaportas; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2769-2791
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Adversarial Noises Are Linearly Separable for (Nearly) Random Neural Networks
Huishuai Zhang, Da Yu, Yiping Lu, Di He; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2792-2804
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Nearly Optimal Latent State Decoding in Block MDPs
Yassir Jedra, Junghyun Lee, Alexandre Proutiere, Se-Young Yun; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2805-2904
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On the Limitations of the Elo, Real-World Games are Transitive, not Additive
Quentin Bertrand, Wojciech Marian Czarnecki, Gauthier Gidel; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2905-2921
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Agnostic PAC Learning of $k$-juntas Using $L_2$-Polynomial Regression
Mohsen Heidari, Wojciech Szpankowski; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2922-2938
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Regularization for Shuffled Data Problems via Exponential Family Priors on the Permutation Group
Zhenbang Wang, Emanuel Ben-David, Martin Slawski; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2939-2959
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Simulator-Based Inference with WALDO: Confidence Regions by Leveraging Prediction Algorithms and Posterior Estimators for Inverse Problems
Luca Masserano, Tommaso Dorigo, Rafael Izbicki, Mikael Kuusela, Ann Lee; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2960-2974
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Analysis of Catastrophic Forgetting for Random Orthogonal Transformation Tasks in the Overparameterized Regime
Daniel Goldfarb, Paul Hand; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2975-2993
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Clustering above Exponential Families with Tempered Exponential Measures
Ehsan Amid, Richard Nock, Manfred K. Warmuth; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:2994-3017
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Mind the (optimality) Gap: A Gap-Aware Learning Rate Scheduler for Adversarial Nets
Hussein Hazimeh, Natalia Ponomareva; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3018-3033
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Learning Physics-Informed Neural Networks without Stacked Back-propagation
Di He, Shanda Li, Wenlei Shi, Xiaotian Gao, Jia Zhang, Jiang Bian, Liwei Wang, Tie-Yan Liu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3034-3047
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An Optimization-based Algorithm for Non-stationary Kernel Bandits without Prior Knowledge
Kihyuk Hong, Yuhang Li, Ambuj Tewari; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3048-3085
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Multi-armed Bandit Experimental Design: Online Decision-making and Adaptive Inference
David Simchi-Levi, Chonghuan Wang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3086-3097
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Squeeze All: Novel Estimator and Self-Normalized Bound for Linear Contextual Bandits
Wonyoung Kim, Myunghee Cho Paik, Min-Hwan Oh; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3098-3124
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Byzantine-Robust Federated Learning with Optimal Statistical Rates
Banghua Zhu, Lun Wang, Qi Pang, Shuai Wang, Jiantao Jiao, Dawn Song, Michael I. Jordan; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3151-3178
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An Unpooling Layer for Graph Generation
Yinglong Guo, Dongmian Zou, Gilad Lerman; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3179-3209
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Online Learning for Traffic Routing under Unknown Preferences
Devansh Jalota, Karthik Gopalakrishnan, Navid Azizan, Ramesh Johari, Marco Pavone; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3210-3229
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Byzantine-Robust Online and Offline Distributed Reinforcement Learning
Yiding Chen, Xuezhou Zhang, Kaiqing Zhang, Mengdi Wang, Xiaojin Zhu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3230-3269
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No-Regret Learning in Two-Echelon Supply Chain with Unknown Demand Distribution
Mengxiao Zhang, Shi Chen, Haipeng Luo, Yingfei Wang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3270-3298
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Mode-constrained Model-based Reinforcement Learning via Gaussian Processes
Aidan Scannell, Carl Henrik Ek, Arthur Richards; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3299-3314
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Generative Oversampling for Imbalanced Data via Majority-Guided VAE
Qingzhong Ai, Pengyun Wang, Lirong He, Liangjian Wen, Lujia Pan, Zenglin Xu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3315-3330
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The Lie-Group Bayesian Learning Rule
Eren Mehmet Kiral, Thomas Moellenhoff, Mohammad Emtiyaz Khan; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3331-3352
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Singular Value Representation: A New Graph Perspective On Neural Networks
Dan Meller, Nicolas Berkouk; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3353-3369
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A Finite Sample Complexity Bound for Distributionally Robust Q-learning
Shengbo Wang, Nian Si, Jose Blanchet, Zhengyuan Zhou; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3370-3398
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Connectivity-contrastive learning: Combining causal discovery and representation learning for multimodal data
Hiroshi Morioka, Aapo Hyvarinen; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3399-3426
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A Bregman Divergence View on the Difference-of-Convex Algorithm
Oisin Faust, Hamza Fawzi, James Saunderson; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3427-3439
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Minority Oversampling for Imbalanced Data via Class-Preserving Regularized Auto-Encoders
Arnab Kumar Mondal, Lakshya Singhal, Piyush Tiwary, Parag Singla, Prathosh AP; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3440-3465
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T-Phenotype: Discovering Phenotypes of Predictive Temporal Patterns in Disease Progression
Yuchao Qin, Mihaela van der Schaar, Changhee Lee; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3466-3492
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Membership Inference Attacks against Synthetic Data through Overfitting Detection
Boris van Breugel, Hao Sun, Zhaozhi Qian, Mihaela van der Schaar; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3493-3514
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Online Learning for Non-monotone DR-Submodular Maximization: From Full Information to Bandit Feedback
Qixin Zhang, Zengde Deng, Zaiyi Chen, Kuangqi Zhou, Haoyuan Hu, Yu Yang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3515-3537
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Robust Variational Autoencoding with Wasserstein Penalty for Novelty Detection
Chieh-Hsin Lai, Dongmian Zou, Gilad Lerman; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3538-3567
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To Impute or not to Impute? Missing Data in Treatment Effect Estimation
Jeroen Berrevoets, Fergus Imrie, Trent Kyono, James Jordon, Mihaela van der Schaar; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3568-3590
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No-regret Sample-efficient Bayesian Optimization for Finding Nash Equilibria with Unknown Utilities
Sebastian Shenghong Tay, Quoc Phong Nguyen, Chuan Sheng Foo, Bryan Kian Hsiang Low; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3591-3619
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Noise-Aware Statistical Inference with Differentially Private Synthetic Data
Ossi Räisä, Joonas Jälkö, Samuel Kaski, Antti Honkela; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3620-3643
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ASkewSGD : An Annealed interval-constrained Optimisation method to train Quantized Neural Networks
Louis Leconte, Sholom Schechtman, Eric Moulines; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3644-3663
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Transport Elliptical Slice Sampling
Alberto Cabezas, Christopher Nemeth; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3664-3676
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Towards Balanced Representation Learning for Credit Policy Evaluation
Yiyan Huang, Cheuk Hang Leung, Shumin Ma, Zhiri Yuan, Qi Wu, Siyi Wang, Dongdong Wang, Zhixiang Huang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3677-3692
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Convergence of Stein Variational Gradient Descent under a Weaker Smoothness Condition
Lukang Sun, Avetik Karagulyan, Peter Richtarik; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3693-3717
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MARS: Masked Automatic Ranks Selection in Tensor Decompositions
Maxim Kodryan, Dmitry Kropotov, Dmitry Vetrov; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3718-3732
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Learning from Multiple Sources for Data-to-Text and Text-to-Data
Song Duong, Alberto Lumbreras, Mike Gartrell, Patrick Gallinari; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3733-3753
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Sparse Bayesian optimization
Sulin Liu, Qing Feng, David Eriksson, Benjamin Letham, Eytan Bakshy; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3754-3774
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On the bias of K-fold cross validation with stable learners
Anass Aghbalou, Anne Sabourin, François Portier; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3775-3794
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Bayesian Convolutional Deep Sets with Task-Dependent Stationary Prior
Yohan Jung, Jinkyoo Park; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3795-3824
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Sample Efficiency of Data Augmentation Consistency Regularization
Shuo Yang, Yijun Dong, Rachel Ward, Inderjit S. Dhillon, Sujay Sanghavi, Qi Lei; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3825-3853
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ANACONDA: An Improved Dynamic Regret Algorithm for Adaptive Non-Stationary Dueling Bandits
Thomas Kleine Buening, Aadirupa Saha; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3854-3878
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Deep Joint Source-Channel Coding with Iterative Source Error Correction
Changwoo Lee, Xiao Hu, Hun-Seok Kim; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3879-3902
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On-Demand Communication for Asynchronous Multi-Agent Bandits
Yu-Zhen Janice Chen, Lin Yang, Xuchuang Wang, Xutong Liu, Mohammad Hajiesmaili, John C. S. Lui, Don Towsley; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3903-3930
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The ELBO of Variational Autoencoders Converges to a Sum of Entropies
Simon Damm, Dennis Forster, Dmytro Velychko, Zhenwen Dai, Asja Fischer, Jörg Lücke; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3931-3960
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Autoencoded sparse Bayesian in-IRT factorization, calibration, and amortized inference for the Work Disability Functional Assessment Battery
Joshua C. Chang, Carson C. Chow, Julia Porcino; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:3961-3976
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Provably Efficient Reinforcement Learning via Surprise Bound
Hanlin Zhu, Ruosong Wang, Jason Lee; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4006-4032
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FAIR: Fair Collaborative Active Learning with Individual Rationality for Scientific Discovery
Xinyi Xu, Zhaoxuan Wu, Arun Verma, Chuan Sheng Foo, Bryan Kian Hsiang Low; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4033-4057
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Sampling From a Schrödinger Bridge
Austin Stromme; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4058-4067
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A Multi-Task Gaussian Process Model for Inferring Time-Varying Treatment Effects in Panel Data
Yehu Chen, Annamaria Prati, Jacob Montgomery, Roman Garnett; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4068-4088
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Deep Grey-Box Modeling With Adaptive Data-Driven Models Toward Trustworthy Estimation of Theory-Driven Models
Naoya Takeishi, Alexandros Kalousis; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4089-4100
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Active Learning for Single Neuron Models with Lipschitz Non-Linearities
Aarshvi Gajjar, Christopher Musco, Chinmay Hegde; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4101-4113
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Exploration in Reward Machines with Low Regret
Hippolyte Bourel, Anders Jonsson, Odalric-Ambrym Maillard, Mohammad Sadegh Talebi; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4114-4146
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On Universal Portfolios with Continuous Side Information
Alankrita Bhatt, J. Jon Ryu, Young-Han Kim; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4147-4163
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Likelihood-Based Generative Radiance Field with Latent Space Energy-Based Model for 3D-Aware Disentangled Image Representation
Yaxuan Zhu, Jianwen Xie, Ping Li; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4164-4180
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The Lauritzen-Chen Likelihood For Graphical Models
Ilya Shpitser; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4181-4195
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Bayesian Strategy-Proof Facility Location via Robust Estimation
Emmanouil Zampetakis, Fred Zhang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4196-4208
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Unsupervised representation learning with recognition-parametrised probabilistic models
William I. Walker, Hugo Soulat, Changmin Yu, Maneesh Sahani; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4209-4230
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Universal Agent Mixtures and the Geometry of Intelligence
Samuel Allen Alexander, David Quarel, Len Du, Marcus Hutter; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4231-4246
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The communication cost of security and privacy in federated frequency estimation
Wei-Ning Chen, Ayfer Ozgur, Graham Cormode, Akash Bharadwaj; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4247-4274
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Learning While Scheduling in Multi-Server Systems With Unknown Statistics: MaxWeight with Discounted UCB
Zixian Yang, R. Srikant, Lei Ying; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4275-4312
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Piecewise Stationary Bandits under Risk Criteria
Sujay Bhatt, Guanhua Fang, Ping Li; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4313-4335
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Does Label Differential Privacy Prevent Label Inference Attacks?
Ruihan Wu, Jin Peng Zhou, Kilian Q. Weinberger, Chuan Guo; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4336-4347
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Understanding Multimodal Contrastive Learning and Incorporating Unpaired Data
Ryumei Nakada, Halil Ibrahim Gulluk, Zhun Deng, Wenlong Ji, James Zou, Linjun Zhang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4348-4380
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Conjugate Gradient Method for Generative Adversarial Networks
Hiroki Naganuma, Hideaki Iiduka; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4381-4408
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Subset verification and search algorithms for causal DAGs
Davin Choo, Kirankumar Shiragur; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4409-4442
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Distributed Offline Policy Optimization Over Batch Data
Han Shen, Songtao Lu, Xiaodong Cui, Tianyi Chen; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4443-4472
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Toward Fairness in Text Generation via Mutual Information Minimization based on Importance Sampling
Rui Wang, Pengyu Cheng, Ricardo Henao; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4473-4485
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Learning Sparse Graphon Mean Field Games
Christian Fabian, Kai Cui, Heinz Koeppl; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4486-4514
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Temporal Graph Neural Networks for Irregular Data
Joel Oskarsson, Per Sidén, Fredrik Lindsten; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4515-4531
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Oblivious near-optimal sampling for multidimensional signals with Fourier constraints
Xingyu Xu, Yuantao Gu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4532-4555
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Isotropic Gaussian Processes on Finite Spaces of Graphs
Viacheslav Borovitskiy, Mohammad Reza Karimi, Vignesh Ram Somnath, Andreas Krause; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4556-4574
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Mean Parity Fair Regression in RKHS
Shaokui Wei, Jiayin Liu, Bing Li, Hongyuan Zha; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4602-4628
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A Unified Perspective on Regularization and Perturbation in Differentiable Subset Selection
Xiangqian Sun, Cheuk Hang Leung, Yijun Li, Qi Wu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4629-4642
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Nyström Method for Accurate and Scalable Implicit Differentiation
Ryuichiro Hataya, Makoto Yamada; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4643-4654
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Fair Representation Learning with Unreliable Labels
Yixuan Zhang, Feng Zhou, Zhidong Li, Yang Wang, Fang Chen; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4655-4667
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Neural Discovery of Permutation Subgroups
Pavan Karjol, Rohan Kashyap, Prathosh AP; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4668-4678
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Feasible Recourse Plan via Diverse Interpolation
Duy Nguyen, Ngoc Bui, Viet Anh Nguyen; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4679-4698
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Computing Abductive Explanations for Boosted Trees
Gilles Audemard, Jean-Marie Lagniez, Pierre Marquis, Nicolas Szczepanski; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4699-4711
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A Statistical Learning Take on the Concordance Index for Survival Analysis
Kevin Elgui, Alex Nowak, Geneviève Robin; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4712-4731
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Equivariant Representation Learning via Class-Pose Decomposition
Giovanni Luca Marchetti, Gustaf Tegnér, Anastasiia Varava, Danica Kragic; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4745-4756
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Approximating a RUM from Distributions on $k$-Slates
Flavio Chierichetti, Mirko Giacchini, Ravi Kumar, Alessandro Panconesi, Andrew Tomkins; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4757-4767
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Mediated Uncoupled Learning and Validation with Bregman Divergences: Loss Family with Maximal Generality
Ikko Yamane, Yann Chevaleyre, Takashi Ishida, Florian Yger; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4768-4801
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Coordinate Descent for SLOPE
Johan Larsson, Quentin Klopfenstein, Mathurin Massias, Jonas Wallin; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4802-4821
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Multi-task Representation Learning with Stochastic Linear Bandits
Leonardo Cella, Karim Lounici, Grégoire Pacreau, Massimiliano Pontil; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4822-4847
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A Sea of Words: An In-Depth Analysis of Anchors for Text Data
Gianluigi Lopardo, Frederic Precioso, Damien Garreau; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4848-4879
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High-Dimensional Private Empirical Risk Minimization by Greedy Coordinate Descent
Paul Mangold, Aurélien Bellet, Joseph Salmon, Marc Tommasi; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4894-4916
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On Generalization of Decentralized Learning with Separable Data
Hossein Taheri, Christos Thrampoulidis; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4917-4945
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Neural Simulated Annealing
Alvaro H.C. Correia, Daniel E. Worrall, Roberto Bondesan; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4946-4962
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Adaptation to Misspecified Kernel Regularity in Kernelised Bandits
Yusha Liu, Aarti Singh; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4963-4985
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Gaussian Processes on Distributions based on Regularized Optimal Transport
François Bachoc, Louis Béthune, Alberto Gonzalez-Sanz, Jean-Michel Loubes; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:4986-5010
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Optimal Contextual Bandits with Knapsacks under Realizability via Regression Oracles
Yuxuan Han, Jialin Zeng, Yang Wang, Yang Xiang, Jiheng Zhang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5011-5035
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Bounding Evidence and Estimating Log-Likelihood in VAE
Łukasz Struski, Marcin Mazur, Paweł Batorski, Przemysław Spurek, Jacek Tabor; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5036-5051
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Privacy-preserving Sparse Generalized Eigenvalue Problem
Lijie Hu, Zihang Xiang, Jiabin Liu, Di Wang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5052-5062
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Asymptotic Bayes risk of semi-supervised multitask learning on Gaussian mixture
Minh-Toan Nguyen, Romain Couillet; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5063-5078
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Manifold Restricted Interventional Shapley Values
Muhammad Faaiz Taufiq, Patrick Blöbaum, Lenon Minorics; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5079-5106
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A Variance-Reduced and Stabilized Proximal Stochastic Gradient Method with Support Identification Guarantees for Structured Optimization
Yutong Dai, Guanyi Wang, Frank E. Curtis, Daniel P. Robinson; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5107-5133
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Complex-to-Real Sketches for Tensor Products with Applications to the Polynomial Kernel
Jonas Wacker, Ruben Ohana, Maurizio Filippone; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5181-5212
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Nonmyopic Multiclass Active Search with Diminishing Returns for Diverse Discovery
Quan Nguyen, Roman Garnett; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5231-5249
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Efficient fair PCA for fair representation learning
Matthäus Kleindessner, Michele Donini, Chris Russell, Muhammad Bilal Zafar; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5250-5270
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Unified Perspective on Probability Divergence via the Density-Ratio Likelihood: Bridging KL-Divergence and Integral Probability Metrics
Masahiro Kato, Masaaki Imaizumi, Kentaro Minami; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5271-5298
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Federated Averaging Langevin Dynamics: Toward a unified theory and new algorithms
Vincent Plassier, Eric Moulines, Alain Durmus; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5299-5356
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Adversarial Random Forests for Density Estimation and Generative Modeling
David S. Watson, Kristin Blesch, Jan Kapar, Marvin N. Wright; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5357-5375
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Smoothly Giving up: Robustness for Simple Models
Tyler Sypherd, Nathaniel Stromberg, Richard Nock, Visar Berisha, Lalitha Sankar; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5376-5410
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A Tighter Problem-Dependent Regret Bound for Risk-Sensitive Reinforcement Learning
Xiaoyan Hu, Ho-Fung Leung; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5411-5437
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Finite time analysis of temporal difference learning with linear function approximation: Tail averaging and regularisation
Gandharv Patil, Prashanth L.A., Dheeraj Nagaraj, Doina Precup; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5438-5448
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Asymptotically Unbiased Off-Policy Policy Evaluation when Reusing Old Data in Nonstationary Environments
Vincent Liu, Yash Chandak, Philip Thomas, Martha White; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5474-5492
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Is interpolation benign for random forest regression?
Ludovic Arnould, Claire Boyer, Erwan Scornet; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5493-5548
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TabLLM: Few-shot Classification of Tabular Data with Large Language Models
Stefan Hegselmann, Alejandro Buendia, Hunter Lang, Monica Agrawal, Xiaoyi Jiang, David Sontag; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5549-5581
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A Faster Sampler for Discrete Determinantal Point Processes
Simon Barthelmé, Nicolas Tremblay, Pierre-Olivier Amblard; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5582-5592
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Faithful Heteroscedastic Regression with Neural Networks
Andrew Stirn, Harm Wessels, Megan Schertzer, Laura Pereira, Neville Sanjana, David Knowles; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5593-5613
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Boosted Off-Policy Learning
Ben London, Levi Lu, Ted Sandler, Thorsten Joachims; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5614-5640
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Symmetric (Optimistic) Natural Policy Gradient for Multi-Agent Learning with Parameter Convergence
Sarath Pattathil, Kaiqing Zhang, Asuman Ozdaglar; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5641-5685
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A Contrastive Approach to Online Change Point Detection
Nikita Puchkin, Valeriia Shcherbakova; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5686-5713
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Active Membership Inference Attack under Local Differential Privacy in Federated Learning
Truc Nguyen, Phung Lai, Khang Tran, NhatHai Phan, My T. Thai; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5714-5730
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Differentially Private Matrix Completion through Low-rank Matrix Factorization
Lingxiao Wang, Boxin Zhao, Mladen Kolar; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5731-5748
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Private Non-Convex Federated Learning Without a Trusted Server
Andrew Lowy, Ali Ghafelebashi, Meisam Razaviyayn; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5749-5786
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Variational Boosted Soft Trees
Tristan Cinquin, Tammo Rukat, Philipp Schmidt, Martin Wistuba, Artur Bekasov; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5787-5801
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Cooperative Inverse Decision Theory for Uncertain Preferences
Zachary Robertson, Hantao Zhang, Sanmi Koyejo; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5854-5868
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Falsification of Internal and External Validity in Observational Studies via Conditional Moment Restrictions
Zeshan Hussain, Ming-Chieh Shih, Michael Oberst, Ilker Demirel, David Sontag; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5869-5898
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Adaptive Dimension Reduction and Variational Inference for Transductive Few-Shot Classification
Yuqing Hu, Stephane Pateux, Vincent Gripon; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5899-5917
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Heavy Sets with Applications to Interpretable Machine Learning Diagnostics
Dmitry Malioutov, Sanjeeb Dash, Dennis Wei; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5918-5930
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Stochastic Mirror Descent for Large-Scale Sparse Recovery
Sasila Ilandarideva, Yannis Bekri, Anatoli Iouditski, Vianney Perchet; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5931-5957
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High Probability Bounds for Stochastic Continuous Submodular Maximization
Evan Becker, Jingdong Gao, Ted Zadouri, Baharan Mirzasoleiman; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5958-5979
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Average Adjusted Association: Efficient Estimation with High Dimensional Confounders
Sung Jae Jun, Sokbae Lee; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5980-5996
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Reinforcement Learning for Adaptive Mesh Refinement
Jiachen Yang, Tarik Dzanic, Brenden Petersen, Jun Kudo, Ketan Mittal, Vladimir Tomov, Jean-Sylvain Camier, Tuo Zhao, Hongyuan Zha, Tzanio Kolev, Robert Anderson, Daniel Faissol; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:5997-6014
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Risk Bounds on Aleatoric Uncertainty Recovery
Yikai Zhang, Jiahe Lin, Fengpei Li, Yeshaya Adler, Kashif Rasul, Anderson Schneider, Yuriy Nevmyvaka; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6015-6036
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Robust and Agnostic Learning of Conditional Distributional Treatment Effects
Nathan Kallus, Miruna Oprescu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6037-6060
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Optimism and Delays in Episodic Reinforcement Learning
Benjamin Howson, Ciara Pike-Burke, Sarah Filippi; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6061-6094
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Delayed Feedback in Generalised Linear Bandits Revisited
Benjamin Howson, Ciara Pike-Burke, Sarah Filippi; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6095-6119
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Stochastic Tree Ensembles for Estimating Heterogeneous Effects
Nikolay Krantsevich, Jingyu He, P. Richard Hahn; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6120-6131
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Minimax Nonparametric Two-Sample Test under Adversarial Losses
Rong Tang, Yun Yang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6132-6165
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Dimensionality Collapse: Optimal Measurement Selection for Low-Error Infinite-Horizon Forecasting
Helmuth Naumer, Farzad Kamalabadi; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6166-6198
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Distill n’ Explain: explaining graph neural networks using simple surrogates
Tamara Pereira, Erik Nascimento, Lucas E. Resck, Diego Mesquita, Amauri Souza; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6199-6214
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Nonstationary Bandit Learning via Predictive Sampling
Yueyang Liu, Benjamin Van Roy, Kuang Xu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6215-6244
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Continuous-Time Decision Transformer for Healthcare Applications
Zhiyue Zhang, Hongyuan Mei, Yanxun Xu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6245-6262
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Dueling RL: Reinforcement Learning with Trajectory Preferences
Aadirupa Saha, Aldo Pacchiano, Jonathan Lee; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6263-6289
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Discrete Langevin Samplers via Wasserstein Gradient Flow
Haoran Sun, Hanjun Dai, Bo Dai, Haomin Zhou, Dale Schuurmans; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6290-6313
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Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph Diffusion
Haotian Ju, Dongyue Li, Aneesh Sharma, Hongyang R. Zhang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6314-6341
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Efficient Planning in Combinatorial Action Spaces with Applications to Cooperative Multi-Agent Reinforcement Learning
Volodymyr Tkachuk, Seyed Alireza Bakhtiari, Johannes Kirschner, Matej Jusup, Ilija Bogunovic, Csaba Szepesvári; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6342-6370
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NODAGS-Flow: Nonlinear Cyclic Causal Structure Learning
Muralikrishnna G Sethuraman, Romain Lopez, Rahul Mohan, Faramarz Fekri, Tommaso Biancalani, Jan-Christian Huetter; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6371-6387
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Revisiting Fair-PAC Learning and the Axioms of Cardinal Welfare
Cyrus Cousins; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6422-6442
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Distributionally Robust Policy Gradient for Offline Contextual Bandits
Zhouhao Yang, Yihong Guo, Pan Xu, Anqi Liu, Animashree Anandkumar; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6443-6462
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A stopping criterion for Bayesian optimization by the gap of expected minimum simple regrets
Hideaki Ishibashi, Masayuki Karasuyama, Ichiro Takeuchi, Hideitsu Hino; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6463-6497
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LOFT: Finding Lottery Tickets through Filter-wise Training
Qihan Wang, Chen Dun, Fangshuo Liao, Chris Jermaine, Anastasios Kyrillidis; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6498-6526
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Provably Efficient Model-Free Algorithms for Non-stationary CMDPs
Honghao Wei, Arnob Ghosh, Ness Shroff, Lei Ying, Xingyu Zhou; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6527-6570
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Precision Recall Cover: A Method For Assessing Generative Models
Fasil Cheema, Ruth Urner; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6571-6594
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Reconstructing Training Data from Model Gradient, Provably
Zihan Wang, Jason Lee, Qi Lei; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6595-6612
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Scalable Spectral Clustering with Group Fairness Constraints
Ji Wang, Ding Lu, Ian Davidson, Zhaojun Bai; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6613-6629
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Efficient and Light-Weight Federated Learning via Asynchronous Distributed Dropout
Chen Dun, Mirian Hipolito, Chris Jermaine, Dimitrios Dimitriadis, Anastasios Kyrillidis; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6630-6660
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Learning with Partial Forgetting in Modern Hopfield Networks
Toshihiro Ota, Ikuro Sato, Rei Kawakami, Masayuki Tanaka, Nakamasa Inoue; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6661-6673
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Efficiently Forgetting What You Have Learned in Graph Representation Learning via Projection
Weilin Cong, Mehrdad Mahdavi; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6674-6703
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Optimizing Pessimism in Dynamic Treatment Regimes: A Bayesian Learning Approach
Yunzhe Zhou, Zhengling Qi, Chengchun Shi, Lexin Li; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6704-6721
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Uncertainty-aware Unsupervised Video Hashing
Yucheng Wang, Mingyuan Zhou, Yu Sun, Xiaoning Qian; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6722-6740
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Incorporating functional summary information in Bayesian neural networks using a Dirichlet process likelihood approach
Vishnu Raj, Tianyu Cui, Markus Heinonen, Pekka Marttinen; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6741-6763
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Structure of Nonlinear Node Embeddings in Stochastic Block Models
Christopher Harker, Aditya Bhaskara; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6764-6782
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On Model Selection Consistency of Lasso for High-Dimensional Ising Models
Xiangming Meng, Tomoyuki Obuchi, Yoshiyuki Kabashima; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6783-6805
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Optimal Sample Complexity Bounds for Non-convex Optimization under Kurdyka-Lojasiewicz Condition
Qian Yu, Yining Wang, Baihe Huang, Qi Lei, Jason D. Lee; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6806-6821
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INO: Invariant Neural Operators for Learning Complex Physical Systems with Momentum Conservation
Ning Liu, Yue Yu, Huaiqian You, Neeraj Tatikola; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6822-6838
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Transport Reversible Jump Proposals
Laurence Davies, Robert Salomone, Matthew Sutton, Chris Drovandi; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6839-6852
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Convex Bounds on the Softmax Function with Applications to Robustness Verification
Dennis Wei, Haoze Wu, Min Wu, Pin-Yu Chen, Clark Barrett, Eitan Farchi; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6853-6878
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Strong Lottery Ticket Hypothesis with $\varepsilon$–perturbation
Zheyang Xiong, Fangshuo Liao, Anastasios Kyrillidis; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6879-6902
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Two-Sample Tests for Inhomogeneous Random Graphs in $L_r$ Norm: Optimality and Asymptotics
Sayak Chatterjee, Dibyendu Saha, Soham Dan, Bhaswar B. Bhattacharya; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6903-6911
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Differentiable Change-point Detection With Temporal Point Processes
Paramita Koley, Harshavardhan Alimi, Shrey Singla, Sourangshu Bhattacharya, Niloy Ganguly, Abir De; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6940-6955
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Recurrent Neural Networks and Universal Approximation of Bayesian Filters
Adrian N. Bishop, Edwin V. Bonilla; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6956-6967
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Thresholded linear bandits
Nishant A. Mehta, Junpei Komiyama, Vamsi K. Potluru, Andrea Nguyen, Mica Grant-Hagen; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6968-7020
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Bayesian Optimization over High-Dimensional Combinatorial Spaces via Dictionary-based Embeddings
Aryan Deshwal, Sebastian Ament, Maximilian Balandat, Eytan Bakshy, Janardhan Rao Doppa, David Eriksson; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7021-7039
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Unifying local and global model explanations by functional decomposition of low dimensional structures
Munir Hiabu, Joseph T. Meyer, Marvin N. Wright; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7040-7060
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SMCP3: Sequential Monte Carlo with Probabilistic Program Proposals
Alexander K. Lew, George Matheos, Tan Zhi-Xuan, Matin Ghavamizadeh, Nishad Gothoskar, Stuart Russell, Vikash K. Mansinghka; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7061-7088
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On double-descent in uncertainty quantification in overparametrized models
Lucas Clarte, Bruno Loureiro, Florent Krzakala, Lenka Zdeborova; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7089-7125
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Learning Treatment Effects from Observational and Experimental Data
Sofia Triantafillou, Fattaneh Jabbari, Gregory F. Cooper; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7126-7146
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On the Accelerated Noise-Tolerant Power Method
Zhiqiang Xu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7147-7175
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Clustering High-dimensional Data with Ordered Weighted $\ell_1$ Regularization
Chandramauli Chakraborty, Sayan Paul, Saptarshi Chakraborty, Swagatam Das; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7176-7189
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Flexible and Efficient Contextual Bandits with Heterogeneous Treatment Effect Oracles
Aldo Gael Carranza, Sanath Kumar Krishnamurthy, Susan Athey; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7190-7212
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Faster Projection-Free Augmented Lagrangian Methods via Weak Proximal Oracle
Dan Garber, Tsur Livney, Shoham Sabach; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7213-7238
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Meta-Learning with Adjoint Methods
Shibo Li, Zheng Wang, Akil Narayan, Robert Kirby, Shandian Zhe; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7239-7251
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Combining Graphical and Algebraic Approaches for Parameter Identification in Latent Variable Structural Equation Models
Ankur Ankan, Inge Wortel, Kenneth Bollen, Johannes Textor; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7252-7264
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Explicit Regularization in Overparametrized Models via Noise Injection
Antonio Orvieto, Anant Raj, Hans Kersting, Francis Bach; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7265-7287
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Efficient Informed Proposals for Discrete Distributions via Newton’s Series Approximation
Yue Xiang, Dongyao Zhu, Bowen Lei, Dongkuan Xu, Ruqi Zhang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7288-7310
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An Homogeneous Unbalanced Regularized Optimal Transport Model with Applications to Optimal Transport with Boundary
Theo Lacombe; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7311-7330
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Prediction-Oriented Bayesian Active Learning
Freddie Bickford Smith, Andreas Kirsch, Sebastian Farquhar, Yarin Gal, Adam Foster, Tom Rainforth; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7331-7348
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Active Exploration via Experiment Design in Markov Chains
Mojmir Mutny, Tadeusz Janik, Andreas Krause; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7349-7374
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But Are You Sure? An Uncertainty-Aware Perspective on Explainable AI
Charles Marx, Youngsuk Park, Hilaf Hasson, Yuyang Wang, Stefano Ermon, Luke Huan; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7375-7391
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Identification of Blackwell Optimal Policies for Deterministic MDPs
Victor Boone, Bruno Gaujal; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7392-7424
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Multi-Fidelity Bayesian Optimization with Unreliable Information Sources
Petrus Mikkola, Julien Martinelli, Louis Filstroff, Samuel Kaski; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7425-7454
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Randomized Greedy Learning for Non-monotone Stochastic Submodular Maximization Under Full-bandit Feedback
Fares Fourati, Vaneet Aggarwal, Christopher Quinn, Mohamed-Slim Alouini; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7455-7471
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Protecting Global Properties of Datasets with Distribution Privacy Mechanisms
Michelle Chen, Olga Ohrimenko; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7472-7491
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Incremental Aggregated Riemannian Gradient Method for Distributed PCA
Xiaolu Wang, Yuchen Jiao, Hoi-To Wai, Yuantao Gu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7492-7510
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Minimax-Bayes Reinforcement Learning
Thomas Kleine Buening, Christos Dimitrakakis, Hannes Eriksson, Divya Grover, Emilio Jorge; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7511-7527
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Retrospective Uncertainties for Deep Models using Vine Copulas
Natasa Tagasovska, Firat Ozdemir, Axel Brando; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7528-7539
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Optimal Algorithms for Latent Bandits with Cluster Structure
Soumyabrata Pal, Arun Sai Suggala, Karthikeyan Shanmugam, Prateek Jain; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7540-7577
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Improved Bound on Generalization Error of Compressed KNN Estimator
Hang Zhang, Ping Li; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7578-7593
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Online Linearized LASSO
Shuoguang Yang, Yuhao Yan, Xiuneng Zhu, Qiang Sun; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7594-7610
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Multi-Agent congestion cost minimization with linear function approximations
Prashant Trivedi, Nandyala Hemachandra; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7611-7643
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Global-Local Regularization Via Distributional Robustness
Hoang Phan, Trung Le, Trung Phung, Anh Tuan Bui, Nhat Ho, Dinh Phung; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7644-7664
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Vector Quantized Time Series Generation with a Bidirectional Prior Model
Daesoo Lee, Sara Malacarne, Erlend Aune; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7665-7693
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Risk-aware linear bandits with convex loss
Patrick Saux, Odalric Maillard; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7723-7754
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One Arrow, Two Kills: A Unified Framework for Achieving Optimal Regret Guarantees in Sleeping Bandits
Pierre Gaillard, Aadirupa Saha, Soham Dan; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7755-7773
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Data Augmentation for Imbalanced Regression
Samuel Stocksieker, Denys Pommeret, Arthur Charpentier; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7774-7799
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Fast Feature Selection with Fairness Constraints
Francesco Quinzan, Rajiv Khanna, Moshik Hershcovitch, Sarel Cohen, Daniel Waddington, Tobias Friedrich, Michael W. Mahoney; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7800-7823
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On the Consistency Rate of Decision Tree Learning Algorithms
Qin-Cheng Zheng, Shen-Huan Lyu, Shao-Qun Zhang, Yuan Jiang, Zhi-Hua Zhou; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7824-7848
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Rank-Based Causal Discovery for Post-Nonlinear Models
Grigor Keropyan, David Strieder, Mathias Drton; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7849-7870
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On the Complexity of Representation Learning in Contextual Linear Bandits
Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7871-7896
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Hierarchical-Hyperplane Kernels for Actively Learning Gaussian Process Models of Nonstationary Systems
Matthias Bitzer, Mona Meister, Christoph Zimmer; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7897-7912
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Revisiting Weighted Strategy for Non-stationary Parametric Bandits
Jing Wang, Peng Zhao, Zhi-Hua Zhou; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7913-7942
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No time to waste: practical statistical contact tracing with few low-bit messages
Rob Romijnders, Yuki M. Asano, Christos Louizos, Max Welling; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7943-7960
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Understanding the Impact of Competing Events on Heterogeneous Treatment Effect Estimation from Time-to-Event Data
Alicia Curth, Mihaela van der Schaar; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7961-7980
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Beyond Performative Prediction: Open-environment Learning with Presence of Corruptions
Jia-Wei Shan, Peng Zhao, Zhi-Hua Zhou; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7981-7998
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Last-Iterate Convergence with Full and Noisy Feedback in Two-Player Zero-Sum Games
Kenshi Abe, Kaito Ariu, Mitsuki Sakamoto, Kentaro Toyoshima, Atsushi Iwasaki; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7999-8028
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Model-Based Uncertainty in Value Functions
Carlos E. Luis, Alessandro G. Bottero, Julia Vinogradska, Felix Berkenkamp, Jan Peters; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8029-8052
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The Role of Codeword-to-Class Assignments in Error-Correcting Codes: An Empirical Study
Itay Evron, Ophir Onn, Tamar Weiss, Hai Azeroual, Daniel Soudry; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8053-8077
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Online Algorithms with Costly Predictions
Marina Drygala, Sai Ganesh Nagarajan, Ola Svensson; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8078-8101
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Adaptive Tuning for Metropolis Adjusted Langevin Trajectories
Lionel Riou-Durand, Pavel Sountsov, Jure Vogrinc, Charles Margossian, Sam Power; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8102-8116
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Further Adaptive Best-of-Both-Worlds Algorithm for Combinatorial Semi-Bandits
Taira Tsuchiya, Shinji Ito, Junya Honda; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8117-8144
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PAC-Bayesian Learning of Optimization Algorithms
Michael Sucker, Peter Ochs; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8145-8164
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Tighter PAC-Bayes Generalisation Bounds by Leveraging Example Difficulty
Felix Biggs, Benjamin Guedj; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8165-8182
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Bures-Wasserstein Barycenters and Low-Rank Matrix Recovery
Tyler Maunu, Thibaut Le Gouic, Philippe Rigollet; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8183-8210
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Pointwise sampling uncertainties on the Precision-Recall curve
Ralph E.Q. Urlus, Max Baak, Stéphane Collot, Ilan Fridman Rojas; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8211-8232
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Exploration in Linear Bandits with Rich Action Sets and its Implications for Inference
Debangshu Banerjee, Avishek Ghosh, Sayak Ray Chowdhury, Aditya Gopalan; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8233-8262
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Nothing but Regrets — Privacy-Preserving Federated Causal Discovery
Osman Mian, David Kaltenpoth, Michael Kamp, Jilles Vreeken; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8263-8278
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Nonparametric Gaussian Process Covariances via Multidimensional Convolutions
Thomas M. Mcdonald, Magnus Ross, Michael T. Smith, Mauricio A. Álvarez; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8279-8293
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Improved Representation Learning Through Tensorized Autoencoders
Pascal Esser, Satyaki Mukherjee, Mahalakshmi Sabanayagam, Debarghya Ghoshdastidar; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8294-8307
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Tensor-based Kernel Machines with Structured Inducing Points for Large and High-Dimensional Data
Frederiek Wesel, Kim Batselier; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8308-8320
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A Targeted Accuracy Diagnostic for Variational Approximations
Yu Wang, Mikolaj Kasprzak, Jonathan H. Huggins; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8351-8372
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Root Cause Identification for Collective Anomalies in Time Series given an Acyclic Summary Causal Graph with Loops
Charles K. Assaad, Imad Ez-Zejjari, Lei Zan; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8395-8404
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Principled Approaches for Private Adaptation from a Public Source
Raef Bassily, Mehryar Mohri, Ananda Theertha Suresh; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8405-8432
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CLIP-Lite: Information Efficient Visual Representation Learning with Language Supervision
Aman Shrivastava, Ramprasaath R. Selvaraju, Nikhil Naik, Vicente Ordonez; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8433-8447
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Surveillance Evasion Through Bayesian Reinforcement Learning
Dongping Qi, David Bindel, Alexander Vladimirsky; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8448-8462
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Overparameterized Random Feature Regression with Nearly Orthogonal Data
Zhichao Wang, Yizhe Zhu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8463-8493
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How Does Pseudo-Labeling Affect the Generalization Error of the Semi-Supervised Gibbs Algorithm?
Haiyun He, Gholamali Aminian, Yuheng Bu, Miguel Rodrigues, Vincent Y. F. Tan; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8494-8520
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Scalable Unbalanced Sobolev Transport for Measures on a Graph
Tam Le, Truyen Nguyen, Kenji Fukumizu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8521-8560
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Discrete Distribution Estimation under User-level Local Differential Privacy
Jayadev Acharya, Yuhan Liu, Ziteng Sun; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8561-8585
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Causal Entropy Optimization
Nicola Branchini, Virginia Aglietti, Neil Dhir, Theodoros Damoulas; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8586-8605
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Loss-Curvature Matching for Dataset Selection and Condensation
Seungjae Shin, Heesun Bae, Donghyeok Shin, Weonyoung Joo, Il-Chul Moon; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8606-8628
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Wasserstein Distributionally Robust Linear-Quadratic Estimation under Martingale Constraints
Kyriakos Lotidis, Nicholas Bambos, Jose Blanchet, Jiajin Li; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8629-8644
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Density Ratio Estimation and Neyman Pearson Classification with Missing Data
Josh Givens, Song Liu, Henry W. J. Reeve; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8645-8681
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Representation Learning in Deep RL via Discrete Information Bottleneck
Riashat Islam, Hongyu Zang, Manan Tomar, Aniket Didolkar, Md Mofijul Islam, Samin Yeasar Arnob, Tariq Iqbal, Xin Li, Anirudh Goyal, Nicolas Heess, Alex Lamb; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8699-8722
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Learning Robust Graph Neural Networks with Limited Supervision
Abdullah Alchihabi, Yuhong Guo; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8723-8733
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Consistent Complementary-Label Learning via Order-Preserving Losses
Shuqi Liu, Yuzhou Cao, Qiaozhen Zhang, Lei Feng, Bo An; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8734-8748
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Tight Regret and Complexity Bounds for Thompson Sampling via Langevin Monte Carlo
Tom Huix, Matthew Zhang, Alain Durmus; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8749-8770
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Nonstochastic Contextual Combinatorial Bandits
Lukas Zierahn, Dirk van der Hoeven, Nicolò Cesa-Bianchi, Gergely Neu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8771-8813
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Probabilistic Conformal Prediction Using Conditional Random Samples
Zhendong Wang, Ruijiang Gao, Mingzhang Yin, Mingyuan Zhou, David Blei; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8814-8836
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Preferential Subsampling for Stochastic Gradient Langevin Dynamics
Srshti Putcha, Christopher Nemeth, Paul Fearnhead; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8837-8856
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On the Calibration of Probabilistic Classifier Sets
Thomas Mortier, Viktor Bengs, Eyke Hüllermeier, Stijn Luca, Willem Waegeman; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8857-8870
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Context-Specific Causal Discovery for Categorical Data Using Staged Trees
Manuele Leonelli, Gherardo Varando; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8871-8888
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Federated Learning for Data Streams
Othmane Marfoq, Giovanni Neglia, Laetitia Kameni, Richard Vidal; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8889-8924
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Adversarial robustness of VAEs through the lens of local geometry
Asif Khan, Amos Storkey; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8954-8967
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Freeze then Train: Towards Provable Representation Learning under Spurious Correlations and Feature Noise
Haotian Ye, James Zou, Linjun Zhang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8968-8990
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Learning to Optimize with Stochastic Dominance Constraints
Hanjun Dai, Yuan Xue, Niao He, Yixin Wang, Na Li, Dale Schuurmans, Bo Dai; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:8991-9009
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SoundSynp: Sound Source Detection from Raw Waveforms with Multi-Scale Synperiodic Filterbanks
Yuhang He, Andrew Markham; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9010-9023
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Second Order Path Variationals in Non-Stationary Online Learning
Dheeraj Baby, Yu-Xiang Wang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9024-9075
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Bayesian Optimization Over Iterative Learners with Structured Responses: A Budget-aware Planning Approach
Syrine Belakaria, Janardhan Rao Doppa, Nicolo Fusi, Rishit Sheth; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9076-9093
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Knowledge Sheaves: A Sheaf-Theoretic Framework for Knowledge Graph Embedding
Thomas Gebhart, Jakob Hansen, Paul Schrater; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9094-9116
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Active Cost-aware Labeling of Streaming Data
Ting Cai, Kirthevasan Kandasamy; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9117-9136
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Krylov–Bellman boosting: Super-linear policy evaluation in general state spaces
Eric Xia, Martin Wainwright; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9137-9166
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SwAMP: Swapped Assignment of Multi-Modal Pairs for Cross-Modal Retrieval
Minyoung Kim; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9167-9190
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A Mini-Block Fisher Method for Deep Neural Networks
Achraf Bahamou, Donald Goldfarb, Yi Ren; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9191-9220
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On the Convergence of Distributed Stochastic Bilevel Optimization Algorithms over a Network
Hongchang Gao, Bin Gu, My T. Thai; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9238-9281
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Pricing against a Budget and ROI Constrained Buyer
Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang, Vahab Mirrokni; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9282-9307
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Improving Dual-Encoder Training through Dynamic Indexes for Negative Mining
Nicholas Monath, Manzil Zaheer, Kelsey Allen, Andrew Mccallum; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9308-9330
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Incentive-aware Contextual Pricing with Non-parametric Market Noise
Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9331-9361
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Coherent Probabilistic Forecasting of Temporal Hierarchies
Syama Sundar Rangapuram, Shubham Kapoor, Rajbir Singh Nirwan, Pedro Mercado, Tim Januschowski, Yuyang Wang, Michael Bohlke-Schneider; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9362-9376
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Optimal robustness-consistency tradeoffs for learning-augmented metrical task systems
Nicolas Christianson, Junxuan Shen, Adam Wierman; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9377-9399
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Randomized geometric tools for anomaly detection in stock markets
Cyril Bachelard, Apostolos Chalkis, Vissarion Fisikopoulos, Elias Tsigaridas; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9400-9416
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ForestPrune: Compact Depth-Pruned Tree Ensembles
Brian Liu, Rahul Mazumder; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9417-9428
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Instance-dependent Sample Complexity Bounds for Zero-sum Matrix Games
Arnab Maiti, Kevin Jamieson, Lillian Ratliff; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9429-9469
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Multiple-policy High-confidence Policy Evaluation
Chris Dann, Mohammad Ghavamzadeh, Teodor V. Marinov; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9470-9487
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Compositional Probabilistic and Causal Inference using Tractable Circuit Models
Benjie Wang, Marta Kwiatkowska; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9488-9498
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Improved Approximation for Fair Correlation Clustering
Sara Ahmadian, Maryam Negahbani; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9499-9516
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Diffusion Generative Models in Infinite Dimensions
Gavin Kerrigan, Justin Ley, Padhraic Smyth; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9538-9563
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MMD-B-Fair: Learning Fair Representations with Statistical Testing
Namrata Deka, Danica J. Sutherland; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9564-9576
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Domain Adaptation under Missingness Shift
Helen Zhou, Sivaraman Balakrishnan, Zachary Lipton; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9577-9606
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Nash Equilibria and Pitfalls of Adversarial Training in Adversarial Robustness Games
Maria-Florina Balcan, Rattana Pukdee, Pradeep Ravikumar, Hongyang Zhang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9607-9636
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Adapting to Latent Subgroup Shifts via Concepts and Proxies
Ibrahim Alabdulmohsin, Nicole Chiou, Alexander D’Amour, Arthur Gretton, Sanmi Koyejo, Matt J. Kusner, Stephen R. Pfohl, Olawale Salaudeen, Jessica Schrouff, Katherine Tsai; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9637-9661
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On the Privacy Risks of Algorithmic Recourse
Martin Pawelczyk, Himabindu Lakkaraju, Seth Neel; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9680-9696
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Reducing Discretization Error in the Frank-Wolfe Method
Zhaoyue Chen, Yifan Sun; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9697-9727
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Improved Sample Complexity Bounds for Distributionally Robust Reinforcement Learning
Zaiyan Xu, Kishan Panaganti, Dileep Kalathil; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9728-9754
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Factorial SDE for Multi-Output Gaussian Process Regression
Daniel P. Jeong, Seyoung Kim; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9755-9772
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Interactive Learning with Pricing for Optimal and Stable Allocations in Markets
Yigit Efe Erginbas, Soham Phade, Kannan Ramchandran; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9773-9806
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Learning to Generalize Provably in Learning to Optimize
Junjie Yang, Tianlong Chen, Mingkang Zhu, Fengxiang He, Dacheng Tao, Yingbin Liang, Zhangyang Wang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9807-9825
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Theory and Algorithm for Batch Distribution Drift Problems
Pranjal Awasthi, Corinna Cortes, Christopher Mohri; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9826-9851
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On The Convergence Of Policy Iteration-Based Reinforcement Learning With Monte Carlo Policy Evaluation
Anna Winnicki, R. Srikant; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9852-9878
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Precision/Recall on Imbalanced Test Data
Hongwei Shang, Jean-Marc Langlois, Kostas Tsioutsiouliklis, Changsung Kang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9879-9891
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Iterative Teaching by Data Hallucination
Zeju Qiu, Weiyang Liu, Tim Z. Xiao, Zhen Liu, Umang Bhatt, Yucen Luo, Adrian Weller, Bernhard Schölkopf; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9892-9913
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Near-Optimal Differentially Private Reinforcement Learning
Dan Qiao, Yu-Xiang Wang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9914-9940
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Doubly Fair Dynamic Pricing
Jianyu Xu, Dan Qiao, Yu-Xiang Wang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:9941-9975
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Probabilities of Causation: Role of Observational Data
Ang Li, Judea Pearl; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10012-10027
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Influence Diagnostics under Self-concordance
Jillian Fisher, Lang Liu, Krishna Pillutla, Yejin Choi, Zaid Harchaoui; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10028-10076
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Theoretically Grounded Loss Functions and Algorithms for Adversarial Robustness
Pranjal Awasthi, Anqi Mao, Mehryar Mohri, Yutao Zhong; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10077-10094
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Large deviations rates for stochastic gradient descent with strongly convex functions
Dragana Bajovic, Dusan Jakovetic, Soummya Kar; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10095-10111
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Stochastic Optimization for Spectral Risk Measures
Ronak Mehta, Vincent Roulet, Krishna Pillutla, Lang Liu, Zaid Harchaoui; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10112-10159
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Improving Adaptive Conformal Prediction Using Self-Supervised Learning
Nabeel Seedat, Alan Jeffares, Fergus Imrie, Mihaela van der Schaar; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10160-10177
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Oracle-free Reinforcement Learning in Mean-Field Games along a Single Sample Path
Muhammad Aneeq Uz Zaman, Alec Koppel, Sujay Bhatt, Tamer Basar; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10178-10206
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Sparsity-Inducing Categorical Prior Improves Robustness of the Information Bottleneck
Anirban Samaddar, Sandeep Madireddy, Prasanna Balaprakash, Taps Maiti, Gustavo de los Campos, Ian Fischer; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10207-10222
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Ideal Abstractions for Decision-Focused Learning
Michael Poli, Stefano Massaroli, Stefano Ermon, Bryan Wilder, Eric Horvitz; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10223-10234
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Probabilistic Querying of Continuous-Time Event Sequences
Alex Boyd, Yuxin Chang, Stephan Mandt, Padhraic Smyth; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10235-10251
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Semantic Strengthening of Neuro-Symbolic Learning
Kareem Ahmed, Kai-Wei Chang, Guy Van den Broeck; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10252-10261
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Fast Variational Estimation of Mutual Information for Implicit and Explicit Likelihood Models
Caleb Dahlke, Sue Zheng, Jason Pacheco; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10262-10278
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SurvivalGAN: Generating Time-to-Event Data for Survival Analysis
Alexander Norcliffe, Bogdan Cebere, Fergus Imrie, Pietro Lió, Mihaela van der Schaar; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10279-10304
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A Conditional Gradient-based Method for Simple Bilevel Optimization with Convex Lower-level Problem
Ruichen Jiang, Nazanin Abolfazli, Aryan Mokhtari, Erfan Yazdandoost Hamedani; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10305-10323
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Stochastic Methods for AUC Optimization subject to AUC-based Fairness Constraints
Yao Yao, Qihang Lin, Tianbao Yang; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10324-10342
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DIET: Conditional independence testing with marginal dependence measures of residual information
Mukund Sudarshan, Aahlad Puli, Wesley Tansey, Rajesh Ranganath; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10343-10367
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Algorithm-Dependent Bounds for Representation Learning of Multi-Source Domain Adaptation
Qi Chen, Mario Marchand; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10368-10394
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Actually Sparse Variational Gaussian Processes
Harry Jake Cunningham, Daniel Augusto de Souza, So Takao, Mark van der Wilk, Marc Peter Deisenroth; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10395-10408
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Competing against Adaptive Strategies in Online Learning via Hints
Aditya Bhaskara, Kamesh Munagala; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10409-10424
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ProbNeRF: Uncertainty-Aware Inference of 3D Shapes from 2D Images
Matthew D. Hoffman, Tuan Anh Le, Pavel Sountsov, Christopher Suter, Ben Lee, Vikash K. Mansinghka, Rif A. Saurous; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10425-10444
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Minimum-Entropy Coupling Approximation Guarantees Beyond the Majorization Barrier
Spencer Compton, Dmitriy Katz, Benjamin Qi, Kristjan Greenewald, Murat Kocaoglu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10445-10469
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Automatic Attention Pruning: Improving and Automating Model Pruning using Attentions
Kaiqi Zhao, Animesh Jain, Ming Zhao; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10470-10486
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Sample Complexity of Distinguishing Cause from Effect
Jayadev Acharya, Sourbh Bhadane, Arnab Bhattacharyya, Saravanan Kandasamy, Ziteng Sun; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10487-10504
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Graph Spectral Embedding using the Geodesic Betweenness Centrality
Shay Deutsch, Stefano Soatto; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10505-10519
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Score-based Quickest Change Detection for Unnormalized Models
Suya Wu, Enmao Diao, Taposh Banerjee, Jie Ding, Vahid Tarokh; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10546-10565
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Dropout-Resilient Secure Multi-Party Collaborative Learning with Linear Communication Complexity
Xingyu Lu, Hasin Us Sami, Başak Güler; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10566-10593
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Reinforcement Learning with Stepwise Fairness Constraints
Zhun Deng, He Sun, Steven Wu, Linjun Zhang, David Parkes; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10594-10618
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Federated Asymptotics: a model to compare federated learning algorithms
Gary Cheng, Karan Chadha, John Duchi; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10650-10689
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Conformalized Unconditional Quantile Regression
Ahmed M. Alaa, Zeshan Hussain, David Sontag; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10690-10702
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Wasserstein Distributional Learning via Majorization-Minimization
Chengliang Tang, Nathan Lenssen, Ying Wei, Tian Zheng; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10703-10731
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HeteRSGD: Tackling Heterogeneous Sampling Costs via Optimal Reweighted Stochastic Gradient Descent
Ziang Chen, Jianfeng Lu, Huajie Qian, Xinshang Wang, Wotao Yin; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10732-10781
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Ultra-marginal Feature Importance: Learning from Data with Causal Guarantees
Joseph Janssen, Vincent Guan, Elina Robeva; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10782-10814
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On the Implicit Geometry of Cross-Entropy Parameterizations for Label-Imbalanced Data
Tina Behnia, Ganesh Ramachandra Kini, Vala Vakilian, Christos Thrampoulidis; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10815-10838
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Convolutional Persistence as a Remedy to Neural Model Analysis
Ekaterina Khramtsova, Guido Zuccon, Xi Wang, Mahsa Baktashmotlagh; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10839-10855
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Uniformly Conservative Exploration in Reinforcement Learning
Wanqiao Xu, Yecheng Ma, Kan Xu, Hamsa Bastani, Osbert Bastani; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10856-10870
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Provable Safe Reinforcement Learning with Binary Feedback
Andrew Bennett, Dipendra Misra, Nathan Kallus; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10871-10900
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Balanced Off-Policy Evaluation for Personalized Pricing
Adam Elmachtoub, Vishal Gupta, Yunfan Zhao; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10901-10917
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Provable Hierarchy-Based Meta-Reinforcement Learning
Kurtland Chua, Qi Lei, Jason Lee; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10918-10967
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A Blessing of Dimensionality in Membership Inference through Regularization
Jasper Tan, Daniel LeJeune, Blake Mason, Hamid Javadi, Richard G. Baraniuk; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10968-10993
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Posterior Tracking Algorithm for Classification Bandits
Koji Tabata, Junpei Komiyama, Atsuyoshi Nakamura, Tamiki Komatsuzaki; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:10994-11022
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Mixtures of All Trees
Nikil Roashan Selvam, Honghua Zhang, Guy Van den Broeck; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11043-11058
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Improving Adversarial Robustness via Joint Classification and Multiple Explicit Detection Classes
Sina Baharlouei, Fatemeh Sheikholeslami, Meisam Razaviyayn, Zico Kolter; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11059-11078
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Performative Prediction with Neural Networks
Mehrnaz Mofakhami, Ioannis Mitliagkas, Gauthier Gidel; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11079-11093
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Benign overfitting of non-smooth neural networks beyond lazy training
Xingyu Xu, Yuantao Gu; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11094-11117
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A New Modeling Framework for Continuous, Sequential Domains
Hailiang Dong, James Amato, Vibhav Gogate, Nicholas Ruozzi; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11118-11131
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TS-UCB: Improving on Thompson Sampling With Little to No Additional Computation
Jackie Baek, Vivek Farias; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11132-11148
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Reward Learning as Doubly Nonparametric Bandits: Optimal Design and Scaling Laws
Kush Bhatia, Wenshuo Guo, Jacob Steinhardt; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11149-11171
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Approximate Regions of Attraction in Learning with Decision-Dependent Distributions
Roy Dong, Heling Zhang, Lillian Ratliff; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11172-11184
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Randomized Primal-Dual Methods with Adaptive Step Sizes
Erfan Yazdandoost Hamedani, Afrooz Jalilzadeh, Necdet S. Aybat; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11185-11212
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Spectral Augmentations for Graph Contrastive Learning
Amur Ghose, Yingxue Zhang, Jianye Hao, Mark Coates; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11213-11266
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Deep Value Function Networks for Large-Scale Multistage Stochastic Programs
Hyunglip Bae, Jinkyu Lee, Woo Chang Kim, Yongjae Lee; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11267-11287
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Optimal Sketching Bounds for Sparse Linear Regression
Tung Mai, Alexander Munteanu, Cameron Musco, Anup Rao, Chris Schwiegelshohn, David Woodruff; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11288-11316
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Average case analysis of Lasso under ultra sparse conditions
Koki Okajima, Xiangming Meng, Takashi Takahashi, Yoshiyuki Kabashima; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11317-11330
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Uncertainty Estimates of Predictions via a General Bias-Variance Decomposition
Sebastian Gruber, Florian Buettner; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11331-11354
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Collision Probability Matching Loss for Disentangling Epistemic Uncertainty from Aleatoric Uncertainty
Hiromi Narimatsu, Mayuko Ozawa, Shiro Kumano; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11355-11370
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Random Features Model with General Convex Regularization: A Fine Grained Analysis with Precise Asymptotic Learning Curves
David Bosch, Ashkan Panahi, Ayca Ozcelikkale, Devdatt Dubhashi; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11371-11414
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Learning to Defer to Multiple Experts: Consistent Surrogate Losses, Confidence Calibration, and Conformal Ensembles
Rajeev Verma, Daniel Barrejon, Eric Nalisnick; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11415-11434
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Spread Flows for Manifold Modelling
Mingtian Zhang, Yitong Sun, Chen Zhang, Steven Mcdonagh; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11435-11456
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Breaking a Classical Barrier for Classifying Arbitrary Test Examples in the Quantum Model
Grzegorz Gluch, Khashayar Barooti, Rüdiger Urbanke; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11457-11488
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Characterizing Polarization in Social Networks using the Signed Relational Latent Distance Model
Nikolaos Nakis, Abdulkadir Celikkanat, Louis Boucherie, Christian Djurhuus, Felix Burmester, Daniel Mathias Holmelund, Monika Frolcová, Morten Mørup; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11489-11505
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Algorithm for Constrained Markov Decision Process with Linear Convergence
Egor Gladin, Maksim Lavrik-Karmazin, Karina Zainullina, Varvara Rudenko, Alexander Gasnikov, Martin Takac; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11506-11533
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Inducing Neural Collapse in Deep Long-tailed Learning
Xuantong Liu, Jianfeng Zhang, Tianyang Hu, He Cao, Yuan Yao, Lujia Pan; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11534-11544
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Encoding Domain Knowledge in Multi-view Latent Variable Models: A Bayesian Approach with Structured Sparsity
Arber Qoku, Florian Buettner; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11545-11562
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Regression as Classification: Influence of Task Formulation on Neural Network Features
Lawrence Stewart, Francis Bach, Quentin Berthet, Jean-Philippe Vert; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11563-11582
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Robust Linear Regression: Gradient-descent, Early-stopping, and Beyond
Meyer Scetbon, Elvis Dohmatob; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11583-11607
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Probing Graph Representations
Mohammad Sadegh Akhondzadeh, Vijay Lingam, Aleksandar Bojchevski; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11630-11649
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Efficient SAGE Estimation via Causal Structure Learning
Christoph Luther, Gunnar König, Moritz Grosse-Wentrup; Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:11650-11670
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