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Editors: Yingzhen Li, Stephan Mandt, Shipra Agrawal, Emtiyaz Khan
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Additive Model Boosting: New Insights and Path(ologie)s
; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1-9
Paths and Ambient Spaces in Neural Loss Landscapes
Daniel Dold, Julius Kobialka, Nicolai Palm, Emanuel Sommer, David Rügamer, Oliver Dürr; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:10-18
Automatically Adaptive Conformal Risk Control
Vincent Blot, Anastasios Nikolas Angelopoulos, Michael Jordan, Nicolas J-B. Brunel; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:19-27
Cost-aware simulation-based inference
Ayush Bharti, Daolang Huang, Samuel Kaski, Francois-Xavier Briol; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:28-36
Generalized Criterion for Identifiability of Additive Noise Models Using Majorization
Aramayis Dallakyan, Yang Ni; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:37-45
Revisiting Online Learning Approach to Inverse Linear Optimization: A Fenchel–Young Loss Perspective and Gap-Dependent Regret Analysis
Shinsaku Sakaue, Han Bao, Taira Tsuchiya; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:46-54
Locally Private Estimation with Public Features
Yuheng Ma, Ke Jia, Hanfang Yang; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:55-63
A Family of Distributions of Random Subsets for Controlling Positive and Negative Dependence
Takahiro Kawashima, Hideitsu Hino; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:64-72
Lower Bounds for Time-Varying Kernelized Bandits
Xu Cai, Jonathan Scarlett; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:73-81
Randomized Iterative Solver as Iterative Refinement: A Simple Fix Towards Backward Stability
Ruihan Xu, Yiping Lu; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:82-90
Flexible Copula-Based Mixed Models in Deep Learning: A Scalable Approach to Arbitrary Marginals
Giora Simchoni, Saharon Rosset; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:91-99
Bayesian Inference in Recurrent Explicit Duration Switching Linear Dynamical Systems
Mikołaj Słupiński; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:100-108
ClusterSC: Advancing Synthetic Control with Donor Selection
Saeyoung Rho, Andrew Tang, Noah Bergam, Rachel Cummings, Vishal Misra; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:109-117
Efficient Estimation of a Gaussian Mean with Local Differential Privacy
Kalinin Nikita, Lukas Steinberger; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:118-126
Credal Two-Sample Tests of Epistemic Uncertainty
Siu Lun Chau, Antonin Schrab, Arthur Gretton, Dino Sejdinovic, Krikamol Muandet; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:127-135
Bayesian Off-Policy Evaluation and Learning for Large Action Spaces
Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:136-144
On the Convergence of Locally Adaptive and Scalable Diffusion-Based Sampling Methods for Deep Bayesian Neural Network Posteriors
Tim Rensmeyer, Oliver Niggemann; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:145-153
Fine-Tuning with Uncertainty-Aware Priors Makes Vision and Language Foundation Models More Reliable
Tim G. J. Rudner, Xiang Pan, Yucen Lily Li, Ravid Shwartz-Ziv, Andrew Gordon Wilson; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:154-162
Optimising Clinical Federated Learning through Mode Connectivity-based Model Aggregation
Anshul Thakur, Soheila Molaei, Patrick Schwab, Danielle Belgrave, Kim Branson, David A. Clifton; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:163-171
S-CFE: Simple Counterfactual Explanations
Shpresim Sadiku, Moritz Wagner, Sai Ganesh Nagarajan, Sebastian Pokutta; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:172-180
A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning
Khimya Khetarpal, Zhaohan Daniel Guo, Bernardo Avila Pires, Yunhao Tang, Clare Lyle, Mark Rowland, Nicolas Heess, Diana L Borsa, Arthur Guez, Will Dabney; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:181-189
Estimation of Large Zipfian Distributions with Sort and Snap
Peter Matthew Jacobs, Anirban Bhattacharya, Debdeep Pati, Lekha Patel, Jeff M. Phillips; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:190-198
Relating Piecewise Linear Kolmogorov Arnold Networks to ReLU Networks
Nandi Schoots, Mattia Jacopo Villani, Niels uit de Bos; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:199-207
$β$-th order Acyclicity Derivatives for DAG Learning
Madhumitha Shridharan, Garud Iyengar; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:208-216
Conditional Generative Learning from Invariant Representations in Multi-Source: Robustness and Efficiency
Guojun Zhu, Sanguo Zhang, Mingyang Ren; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:217-225
Harnessing the Power of Vicinity-Informed Analysis for Classification under Covariate Shift
Mitsuhiro Fujikawa, Youhei Akimoto, Jun Sakuma, Kazuto Fukuchi; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:226-234
Bayesian Gaussian Process ODEs via Double Normalizing Flows
JIAN XU, Shian Du, Junmei Yang, Xinghao Ding, Delu Zeng, John Paisley; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:235-243
The Local Learning Coefficient: A Singularity-Aware Complexity Measure
Edmund Lau, Zach Furman, George Wang, Daniel Murfet, Susan Wei; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:244-252
Density Ratio Estimation via Sampling along Generalized Geodesics on Statistical Manifolds
Masanari Kimura, Howard Bondell; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:253-261
Choice is what matters after Attention
Chenhan Fu, Guoming Wang, Juncheng Li, Rongxing Lu, Siliang Tang; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:262-270
The Pivoting Framework: Frank-Wolfe Algorithms with Active Set Size Control
Mathieu Besançon, Sebastian Pokutta, Elias Samuel Wirth; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:271-279
Accelerated Methods for Riemannian Min-Max Optimization Ensuring Bounded Geometric Penalties
David Martínez-Rubio, Christophe Roux, Christopher Criscitiello, Sebastian Pokutta; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:280-288
Almost linear time differentially private release of synthetic graphs
Zongrui Zou, Jingcheng Liu, Jalaj Upadhyay; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:289-297
Adversarial Training in High-Dimensional Regression: Generated Data and Neural Networks
Yue Xing; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:298-306
A Bias-Variance Decomposition for Ensembles over Multiple Synthetic Datasets
Ossi Räisä, Antti Honkela; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:307-315
Approximate information maximization for bandit games
Alex Barbier Chebbah, Christian L. Vestergaard, Jean-Baptiste Masson, Etienne Boursier; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:316-324
Disentangling impact of capacity, objective, batchsize, estimators, and step-size on flow VI
Abhinav Agrawal, Justin Domke; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:325-333
Generalization Lower Bounds for GD and SGD in Smooth Stochastic Convex Optimization
Peiyuan Zhang, Jiaye Teng, Jingzhao Zhang; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:334-342
Learning in Herding Mean Field Games: Single-Loop Algorithm with Finite-Time Convergence Analysis
Sihan Zeng, Sujay Bhatt, Alec Koppel, Sumitra Ganesh; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:343-351
Strong Screening Rules for Group-based SLOPE Models
Fabio Feser, Marina Evangelou; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:352-360
Infinite-Horizon Reinforcement Learning with Multinomial Logit Function Approximation
Jaehyun Park, Junyeop Kwon, Dabeen Lee; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:361-369
Constrained Multi-objective Bayesian Optimization through Optimistic Constraints Estimation
Diantong Li, Fengxue Zhang, Chong Liu, Yuxin Chen; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:370-378
Prior-Dependent Allocations for Bayesian Fixed-Budget Best-Arm Identification in Structured Bandits
Nicolas Nguyen, Imad Aouali, András György, Claire Vernade; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:379-387
Nyström Kernel Stein Discrepancy
Florian Kalinke, Zoltán Szabó, Bharath Sriperumbudur; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:388-396
Some Targets Are Harder to Identify than Others: Quantifying the Target-dependent Membership Leakage
Achraf Azize, Debabrota Basu; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:397-405
Near-Optimal Algorithm for Non-Stationary Kernelized Bandits
Shogo Iwazaki, Shion Takeno; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:406-414
No-Regret Bayesian Optimization with Stochastic Observation Failures
Shogo Iwazaki, Tomohiko Tanabe, Mitsuru Irie, Shion Takeno, Kota Matsui, Yu Inatsu; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:415-423
Nonparametric Factor Analysis and Beyond
Yujia Zheng, Yang Liu, Jiaxiong Yao, Yingyao Hu, Kun Zhang; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:424-432
Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization
Deep Chakraborty, Yann LeCun, Tim G. J. Rudner, Erik Learned-Miller; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:433-441
Scalable Inference for Bayesian Multinomial Logistic-Normal Dynamic Linear Models
Manan Saxena, Tinghua Chen, Justin D Silverman; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:442-450
Inverse Optimization with Prediction Market: A Characterization of Scoring Rules for Elciting System States
Han Bao, Shinsaku Sakaue; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:451-459
HAVER: Instance-Dependent Error Bounds for Maximum Mean Estimation and Applications to Q-Learning and Monte Carlo Tree Search
Tuan Nguyen, Jay Barrett, Kwang-Sung Jun; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:460-468
Ant Colony Sampling with GFlowNets for Combinatorial Optimization
Minsu Kim, Sanghyeok Choi, Hyeonah Kim, Jiwoo Son, Jinkyoo Park, Yoshua Bengio; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:469-477
Function-Space MCMC for Bayesian Wide Neural Networks
Lucia Pezzetti, Stefano Favaro, Stefano Peluchetti; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:478-486
A Theoretical Framework for Preventing Class Collapse in Supervised Contrastive Learning
Chungpa Lee, Jeongheon Oh, Kibok Lee, Jy-yong Sohn; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:487-495
Signed Graph Autoencoder for Explainable and Polarization-Aware Network Embeddings
Nikolaos Nakis, Chrysoula Kosma, Giannis Nikolentzos, Michail Chatzianastasis, Iakovos Evdaimon, Michalis Vazirgiannis; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:496-504
On the Asymptotic Mean Square Error Optimality of Diffusion Models
Benedikt Fesl, Benedikt Böck, Florian Strasser, Michael Baur, Michael Joham, Wolfgang Utschick; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:505-513
Adaptive Extragradient Methods for Root-finding Problems under Relaxed Assumptions
Yang Luo, Michael J O’Neill; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:514-522
Fourier Circuits in Neural Networks and Transformers: A Case Study of Modular Arithmetic with Multiple Inputs
Chenyang Li, Yingyu Liang, Zhenmei Shi, Zhao Song, Tianyi Zhou; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:523-531
Signature Isolation Forest
Marta Campi, Guillaume Staerman, Gareth W. Peters, Tomoko Masui; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:532-540
Elastic Representation: Mitigating Spurious Correlations for Group Robustness
Tao Wen, Zihan Wang, Quan Zhang, Qi Lei; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:541-549
Scalable spectral representations for multiagent reinforcement learning in network MDPs
Zhaolin Ren, Runyu Zhang, Bo Dai, Na Li; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:550-558
Bridging Domains with Approximately Shared Features
Ziliang Samuel Zhong, Xiang Pan, Qi Lei; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:559-567
Epistemic Uncertainty and Excess Risk in Variational Inference
Futoshi Futami; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:568-576
Learning Identifiable Structures Helps Avoid Bias in DNN-based Supervised Causal Learning
Jiaru Zhang, Rui Ding, Qiang Fu, Huang Bojun, Zizhen Deng, Yang Hua, Haibing Guan, Shi Han, Dongmei Zhang; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:577-585
Selecting the Number of Communities for Weighted Degree-Corrected Stochastic Block Models
Yucheng Liu, Xiaodong Li; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:586-594
Empirical Error Estimates for Graph Sparsification
Siyao Wang, Miles E. Lopes; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:595-603
On the Geometry and Optimization of Polynomial Convolutional Networks
Vahid Shahverdi, Giovanni Luca Marchetti, Kathlén Kohn; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:604-612
Data Reconstruction Attacks and Defenses: A Systematic Evaluation
Sheng Liu, Zihan Wang, Yuxiao Chen, Qi Lei; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:613-621
Locally Private Sampling with Public Data
Behnoosh Zamanlooy, Mario Diaz, Shahab Asoodeh; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:622-630
Reliable and Scalable Variable Importance Estimation via Warm-start and Early Stopping
Zexuan Sun, Garvesh Raskutti; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:631-639
Reinforcement Learning for Adaptive MCMC
Congye Wang, Wilson Ye Chen, Heishiro Kanagawa, Chris J. Oates; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:640-648
Prediction-Centric Uncertainty Quantification via MMD
Zheyang Shen, Jeremias Knoblauch, Samuel Power, Chris J. Oates; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:649-657
Harnessing Causality in Reinforcement Learning with Bagged Decision Times
Daiqi Gao, Hsin-Yu Lai, Predrag Klasnja, Susan Murphy; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:658-666
Learning the Pareto Front Using Bootstrapped Observation Samples
Wonyoung Kim, Garud Iyengar, Assaf Zeevi; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:667-675
FedBaF: Federated Learning Aggregation Biased by a Foundation Model
Jong-Ik Park, Srinivasa Pranav, Jose M F Moura, Carlee Joe-Wong; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:676-684
A Generalized Theory of Mixup for Structure-Preserving Synthetic Data
Chungpa Lee, Jongho Im, Joseph H.T. Kim; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:685-693
On the Sample Complexity of Next-Token Prediction
Oğuz Kaan Yüksel, Nicolas Flammarion; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:694-702
Amortized Probabilistic Conditioning for Optimization, Simulation and Inference
Paul Edmund Chang, Nasrulloh Ratu Bagus Satrio Loka, Daolang Huang, Ulpu Remes, Samuel Kaski, Luigi Acerbi; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:703-711
Steering No-Regret Agents in MFGs under Model Uncertainty
Leo Widmer, Jiawei Huang, Niao He; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:712-720
Bridging Multiple Worlds: Multi-marginal Optimal Transport for Causal Partial-identification Problem
Zijun Gao, Shu Ge, Jian Qian; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:721-729
The Polynomial Iteration Complexity for Variance Exploding Diffusion Models: Elucidating SDE and ODE Samplers
Ruofeng Yang, Bo Jiang, Shuai Li; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:730-738
To Give or Not to Give? The Impacts of Strategically Withheld Recourse
Yatong Chen, Andrew Estornell, Yevgeniy Vorobeychik, Yang Liu; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:739-747
Optimal estimation of linear non-Gaussian structure equation models
Sunmin Oh, Seungsu Han, Gunwoong Park; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:748-756
Stein Boltzmann Sampling: A Variational Approach for Global Optimization
Gaëtan Serré, Argyris Kalogeratos, Nicolas Vayatis; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:757-765
Learning signals defined on graphs with optimal transport and Gaussian process regression
Raphael Carpintero Perez, Sébastien Da Veiga, Josselin Garnier, Brian Staber; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:766-774
Score matching for bridges without learning time-reversals
Elizabeth Louise Baker, Moritz Schauer, Stefan Sommer; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:775-783
Safe exploration in reproducing kernel Hilbert spaces
Abdullah Tokmak, Kiran G. Krishnan, Thomas B. Schön, Dominik Baumann; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:784-792
Ordered $\mathcalV$-information Growth: A Fresh Perspective on Shared Information
Rohan Ghosh, Mehul Motani; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:793-801
On Tradeoffs in Learning-Augmented Algorithms
Ziyad Benomar, Vianney Perchet; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:802-810
Cubic regularized subspace Newton for non-convex optimization
Jim Zhao, Nikita Doikov, Aurelien Lucchi; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:811-819
Consistent Validation for Predictive Methods in Spatial Settings
David R. Burt, Yunyi Shen, Tamara Broderick; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:820-828
Get rid of your constraints and reparametrize: A study in NNLS and implicit bias
Hung-Hsu Chou, Johannes Maly, Claudio Mayrink Verdun, Bernardo Freitas Paulo da Costa, Heudson Mirandola; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:829-837
Collaborative non-parametric two-sample testing
Alejandro David De la Concha Duarte, Nicolas Vayatis, Argyris Kalogeratos; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:838-846
Tamed Langevin sampling under weaker conditions
Iosif Lytras, Panayotis Mertikopoulos; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:847-855
Entropic Matching for Expectation Propagation of Markov Jump Processes
Yannick Eich, Bastian Alt, Heinz Koeppl; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:856-864
Global Group Fairness in Federated Learning via Function Tracking
Yves Rychener, Daniel Kuhn, Yifan Hu; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:865-873
Near-Optimal Sample Complexity in Reward-Free Kernel-based Reinforcement Learning
Aya Kayal, Sattar Vakili, Laura Toni, Alberto Bernacchia; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:874-882
Poisoning Bayesian Inference via Data Deletion and Replication
Matthieu Carreau, Roi Naveiro, William N. Caballero; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:883-891
Near-optimal algorithms for private estimation and sequential testing of collision probability
Robert Istvan Busa-Fekete, Umar Syed; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:892-900
Fundamental Limits of Perfect Concept Erasure
Somnath Basu Roy Chowdhury, Kumar Avinava Dubey, Ahmad Beirami, Rahul Kidambi, Nicholas Monath, Amr Ahmed, Snigdha Chaturvedi; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:901-909
Perfect Recovery for Random Geometric Graph Matching with Shallow Graph Neural Networks
Suqi Liu, Morgane Austern; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:910-918
Microfoundation inference for strategic prediction
Daniele Bracale, Subha Maity, Felipe Maia Polo, Seamus Somerstep, Moulinath Banerjee, Yuekai Sun; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:919-927
Heterogeneous Graph Structure Learning through the Lens of Data-generating Processes
Keyue Jiang, Bohan Tang, Xiaowen Dong, Laura Toni; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:928-936
Superiority of Multi-Head Attention: A Theoretical Study in Shallow Transformers in In-Context Linear Regression
Yingqian Cui, Jie Ren, Pengfei He, Hui Liu, Jiliang Tang, Yue Xing; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:937-945
Balls-and-Bins Sampling for DP-SGD
Lynn Chua, Badih Ghazi, Charlie Harrison, Pritish Kamath, Ravi Kumar, Ethan Jacob Leeman, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:946-954
Distance Estimation for High-Dimensional Discrete Distributions
Kuldeep S. Meel, Gunjan Kumar, Yash Pote; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:955-963
Type Information-Assisted Self-Supervised Knowledge Graph Denoising
Jiaqi Sun, Yujia Zheng, Xinshuai Dong, Haoyue Dai, Kun Zhang; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:964-972
Learning the Distribution Map in Reverse Causal Performative Prediction
Daniele Bracale, Subha Maity, Yuekai Sun, Moulinath Banerjee; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:973-981
Optimizing Neural Network Training and Quantization with Rooted Logistic Objectives
Zhu Wang, Praveen Raj Veluswami, Harsh Mishra, Sathya N. Ravi; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:982-990
Planning and Learning in Risk-Aware Restless Multi-Arm Bandits
Nima Akbarzadeh, Yossiri Adulyasak, Erick Delage; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:991-999
Pareto Set Identification With Posterior Sampling
Cyrille Kone, Marc Jourdan, Emilie Kaufmann; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1000-1008
Convergence Analysis for General Probability Flow ODEs of Diffusion Models in Wasserstein Distances
Xuefeng Gao, Lingjiong Zhu; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1009-1017
Geometry-Aware Generative Autoencoders for Warped Riemannian Metric Learning and Generative Modeling on Data Manifolds
Xingzhi Sun, Danqi Liao, Kincaid MacDonald, Yanlei Zhang, Guillaume Huguet, Guy Wolf, Ian Adelstein, Tim G. J. Rudner, Smita Krishnaswamy; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1018-1026
Q-function Decomposition with Intervention Semantics for Factored Action Spaces
Junkyu Lee, Tian Gao, Elliot Nelson, Miao Liu, Debarun Bhattacharjya, Songtao Lu; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1027-1035
HAR-former: Hybrid Transformer with an Adaptive Time-Frequency Representation Matrix for Long-Term Series Forecasting
Kenghao Zheng, Zi Long, Shuxin Wang; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1036-1044
Bayesian Decision Theory on Decision Trees: Uncertainty Evaluation and Interpretability
Yuta Nakahara, Shota Saito, Naoki Ichijo, Koki Kazama, Toshiyasu Matsushima; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1045-1053
Hybrid Transfer Reinforcement Learning: Provable Sample Efficiency from Shifted-Dynamics Data
Chengrui Qu, Laixi Shi, Kishan Panaganti, Pengcheng You, Adam Wierman; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1054-1062
Trustworthy assessment of heterogeneous treatment effect estimator via analysis of relative error
Zijun Gao; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1063-1071
Learning-Augmented Algorithms for Online Concave Packing and Convex Covering Problems
Elena Grigorescu, Young-San Lin, Maoyuan Song; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1072-1080
On the Power of Adaptive Weighted Aggregation in Heterogeneous Federated Learning and Beyond
Dun Zeng, Zenglin Xu, SHIYU LIU, Yu Pan, Qifan Wang, Xiaoying Tang; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1081-1089
Prior-Fitted Networks Scale to Larger Datasets When Treated as Weak Learners
Yuxin Wang, Botian Jiang, Yiran Guo, Quan Gan, David Wipf, Xuanjing Huang, Xipeng Qiu; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1090-1098
Locally Optimal Descent for Dynamic Stepsize Scheduling
Gilad Yehudai, Alon Cohen, Amit Daniely, Yoel Drori, Tomer Koren, Mariano Schain; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1099-1107
Online Student-$t$ Processes with an Overall-local Scale Structure for Modelling Non-stationary Data
Taole Sha, Michael Minyi Zhang; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1108-1116
Policy Teaching via Data Poisoning in Learning from Human Preferences
Andi Nika, Jonathan Nöther, Debmalya Mandal, Parameswaran Kamalaruban, Adish Singla, Goran Radanovic; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1117-1125
Model selection for behavioral learning data and applications to contextual bandits
Julien Aubert, Louis Köhler, Luc Lehéricy, Giulia Mezzadri, Patricia Reynaud-Bouret; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1126-1134
Distributional Counterfactual Explanations With Optimal Transport
Lei You, Lele Cao, Mattias Nilsson, Bo Zhao, Lei Lei; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1135-1143
$f$-PO: Generalizing Preference Optimization with $f$-divergence Minimization
Jiaqi Han, Mingjian Jiang, Yuxuan Song, Stefano Ermon, Minkai Xu; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1144-1152
Variational Inference on the Boolean Hypercube with the Quantum Entropy
Eliot Beyler, Francis Bach; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1153-1161
Optimal Multi-Objective Best Arm Identification with Fixed Confidence
Zhirui Chen, P. N. Karthik, Yeow Meng Chee, Vincent Y. F. Tan; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1162-1170
Symmetry-Based Structured Matrices for Efficient Approximately Equivariant Networks
Ashwin Samudre, Mircea Petrache, Brian Nord, Shubhendu Trivedi; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1171-1179
Evaluating Prediction-based Interventions with Human Decision Makers In Mind
Inioluwa Deborah Raji, Lydia T. Liu; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1180-1188
Bandit Pareto Set Identification in a Multi-Output Linear Model
Cyrille Kone, Emilie Kaufmann, Laura Richert; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1189-1197
posteriordb: Testing, Benchmarking and Developing Bayesian Inference Algorithms
Måns Magnusson, Jakob Torgander, Paul-Christian Bürkner, Lu Zhang, Bob Carpenter, Aki Vehtari; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1198-1206
Efficient Optimization Algorithms for Linear Adversarial Training
Antonio H. Ribeiro, Thomas B. Schön, Dave Zachariah, Francis Bach; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1207-1215
Learning a Single Index Model from Anisotropic Data with Vanilla Stochastic Gradient Descent
Guillaume Braun, Minh Ha Quang, Masaaki Imaizumi; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1216-1224
A primer on linear classification with missing data
Angel David REYERO LOBO, Alexis Ayme, Claire Boyer, Erwan Scornet; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1225-1233
Robust Score Matching
Richard Schwank, Andrew McCormack, Mathias Drton; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1234-1242
On the Relationship Between Robustness and Expressivity of Graph Neural Networks
Lorenz Kummer, Wilfried N. Gansterer, Nils Morten Kriege; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1243-1251
Parameter estimation in state space models using particle importance sampling
Yuxiong Gao, Wentao Li, Rong Chen; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1252-1260
Class Imbalance in Anomaly Detection: Learning from an Exactly Solvable Model
Francesco Saverio Pezzicoli, Valentina Ros, François P. Landes, Marco Baity-Jesi; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1261-1269
Unbiased Quantization of the $L_1$ Ball for Communication-Efficient Distributed Mean Estimation
Nithish Suresh Babu, Ritesh Kumar, Shashank Vatedka; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1270-1278
MING: A Functional Approach to Learning Molecular Generative Models
Van Khoa Nguyen, Maciej Falkiewicz, Giangiacomo Mercatali, Alexandros Kalousis; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1279-1287
Sequential Kernelized Stein Discrepancy
Diego Martinez-Taboada, Aaditya Ramdas; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1288-1296
SubSearch: Robust Estimation and Outlier Detection for Stochastic Block Models via Subgraph Search
Leonardo Bianco, Christine Keribin, Zacharie Naulet; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1297-1305
Optimal downsampling for Imbalanced Classification with Generalized Linear Models
Yan Chen, Jose Blanchet, Krzysztof Dembczynski, Laura Fee Nern, Aaron Eliasib Flores; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1306-1314
Federated UCBVI: Communication-Efficient Federated Regret Minimization with Heterogeneous Agents
Safwan Labbi, Daniil Tiapkin, Lorenzo Mancini, Paul Mangold, Eric Moulines; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1315-1323
Noisy Low-Rank Matrix Completion via Transformed $L_1$ Regularization and its Theoretical Properties
Kun Zhao, Jiayi Wang, Yifei Lou; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1324-1332
Representer Theorems for Metric and Preference Learning: Geometric Insights and Algorithms
Peyman Morteza; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1333-1341
UNHaP: Unmixing Noise from Hawkes Processes
Virginie Loison, Guillaume Staerman, Thomas Moreau; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1342-1350
Axiomatic Explainer Globalness via Optimal Transport
Davin Hill, Joshua Bone, Aria Masoomi, Max Torop, Jennifer Dy; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1351-1359
Integer Programming Based Methods and Heuristics for Causal Graph Learning
Sanjeeb Dash, Joao Goncalves, Tian Gao; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1360-1368
The VampPrior Mixture Model
Andrew A. Stirn, David A. Knowles; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1369-1377
MEDUSA: Medical Data Under Shadow Attacks via Hybrid Model Inversion
Asfandyar Azhar, Paul Thielen, Curtis Langlotz; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1378-1386
Proximal Sampler with Adaptive Step Size
Bo Yuan, Jiaojiao Fan, Jiaming Liang, Yongxin Chen; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1387-1395
Rate of Model Collapse in Recursive Training
Ananda Theertha Suresh, Andrew Thangaraj, Aditya Nanda Kishore Khandavally; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1396-1404
A Shared Low-Rank Adaptation Approach to Personalized RLHF
Renpu Liu, Peng Wang, Donghao Li, Cong Shen, Jing Yang; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1405-1413
Differentially private algorithms for linear queries via stochastic convex optimization
Giorgio Micali, Clement LEZANE, Annika Betken; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1414-1422
Is Merging Worth It? Securely Evaluating the Information Gain for Causal Dataset Acquisition
Jake Fawkes, Lucile Ter-Minassian, Desi R. Ivanova, Uri Shalit, Christopher C. Holmes; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1423-1431
Recursive Learning of Asymptotic Variational Objectives
Alessandro Mastrototaro, Mathias Müller, Jimmy Olsson; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1432-1440
Improving Stochastic Cubic Newton with Momentum
El Mahdi Chayti, Nikita Doikov, Martin Jaggi; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1441-1449
Adaptive Convergence Rates for Log-Concave Maximum Likelihood
Gil Kur, Aditya Guntuboyina; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1450-1458
Learning to Negotiate via Voluntary Commitment
Shuhui Zhu, Baoxiang Wang, Sriram Ganapathi Subramanian, Pascal Poupart; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1459-1467
Differentiable Calibration of Inexact Stochastic Simulation Models via Kernel Score Minimization
Ziwei Su, Diego Klabjan; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1468-1476
Fully Dynamic Adversarially Robust Correlation Clustering in Polylogarithmic Update Time
Vladimir Braverman, Prathamesh Dharangutte, Shreyas Pai, Vihan Shah, Chen Wang; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1477-1485
On Distributional Discrepancy for Experimental Design with General Assignment Probabilities
Anup Rao, Peng Zhang; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1486-1494
Dynamic DBSCAN with Euler Tour Sequences
Seiyun Shin, Ilan Shomorony, Peter Macgregor; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1495-1503
Differentially Private Range Queries with Correlated Input Perturbation
Prathamesh Dharangutte, Jie Gao, Ruobin Gong, Guanyang Wang; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1504-1512
An Adaptive Method for Weak Supervision with Drifting Data
Alessio Mazzetto, Reza Esfandiarpoor, Akash Singirikonda, Eli Upfal, Stephen Bach; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1513-1521
On the Inherent Privacy of Zeroth-Order Projected Gradient Descent
Devansh Gupta, Meisam Razaviyayn, Vatsal Sharan; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1522-1530
Transformers are Provably Optimal In-context Estimators for Wireless Communications
Vishnu Teja Kunde, Vicram Rajagopalan, Chandra Shekhara Kaushik Valmeekam, Krishna Narayanan, Jean-Francois Chamberland, Dileep Kalathil, Srinivas Shakkottai; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1531-1539
Multi-Player Approaches for Dueling Bandits
Or Raveh, Junya Honda, Masashi Sugiyama; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1540-1548
Improved dependence on coherence in eigenvector and eigenvalue estimation error bounds
Hao Yan, Keith Levin; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1549-1557
Provable Benefits of Task-Specific Prompts for In-context Learning
Xiangyu Chang, Yingcong Li, Muti Kara, Samet Oymak, Amit Roy-Chowdhury; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1558-1566
Neural Point Processes for Pixel-wise Regression
Chengzhi Shi, Gözde Özcan, Miquel Sirera Perelló, Yuanyuan Li, Nina Iftikhar Shamsi, Stratis Ioannidis; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1567-1575
Importance-weighted Positive-unlabeled Learning for Distribution Shift Adaptation
Atsutoshi Kumagai, Tomoharu Iwata, Hiroshi Takahashi, Taishi Nishiyama, Yasuhiro Fujiwara; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1576-1584
Minimum Empirical Divergence for Sub-Gaussian Linear Bandits
Kapilan Balagopalan, Kwang-Sung Jun; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1585-1593
Dissecting the Impact of Model Misspecification in Data-Driven Optimization
Adam N. Elmachtoub, Henry Lam, Haixiang Lan, Haofeng Zhang; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1594-1602
ROTI-GCV: Generalized Cross-Validation for right-ROTationally Invariant Data
Kevin Luo, Yufan Li, Pragya Sur; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1603-1611
Clustered Invariant Risk Minimization
Tomoya Murata, Atsushi Nitanda, Taiji Suzuki; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1612-1620
Towards a mathematical theory for consistency training in diffusion models
Gen Li, Zhihan Huang, Yuting Wei; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1621-1629
Training LLMs with MXFP4
Albert Tseng, Tao Yu, Youngsuk Park; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1630-1638
Multi-agent Multi-armed Bandit Regret Complexity and Optimality
Mengfan Xu, Diego Klabjan; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1639-1647
Models That Are Interpretable But Not Transparent
Chudi Zhong, Panyu Chen, Cynthia Rudin; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1648-1656
Reinforcement Learning with Intrinsically Motivated Feedback Graph for Lost-sales Inventory Control
Zifan LIU, Xinran Li, Shibo Chen, Gen Li, Jiashuo Jiang, Jun Zhang; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1657-1665
AxlePro: Momentum-Accelerated Batched Training of Kernel Machines
Yiming Zhang, Parthe Pandit; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1666-1674
A Likelihood Based Approach for Watermark Detection
Xingchi Li, Guanxun Li, Xianyang Zhang; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1675-1683
What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization
Yufeng Zhang, Fengzhuo Zhang, Zhuoran Yang, Zhaoran Wang; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1684-1692
Bayesian Circular Regression with von Mises Quasi-Processes
Yarden Cohen, Alexandre Khae Wu Navarro, Jes Frellsen, Richard E. Turner, Raziel Riemer, Ari Pakman; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1693-1701
Cross Validation for Correlated Data in Classification Models
Oren Yuval, Saharon Rosset; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1702-1710
Post-processing for Fair Regression via Explainable SVD
Zhiqun Zuo, Ding Zhu, Mohammad Mahdi Khalili; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1711-1719
Truncated Inverse-Lévy Measure Representation of the Beta Process
Junyi Zhang, Angelos Dassios, Zhong Chong, Qiufei Yao; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1720-1728
Consistent Amortized Clustering via Generative Flow Networks
Irit Chelly, Roy Uziel, Oren Freifeld, Ari Pakman; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1729-1737
Adaptive RKHS Fourier Features for Compositional Gaussian Process Models
Xinxing Shi, Thomas Baldwin-McDonald, Mauricio A Álvarez; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1738-1746
Statistical Inference for Feature Selection after Optimal Transport-based Domain Adaptation
Nguyen Thang Loi, Duong Tan Loc, Vo Nguyen Le Duy; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1747-1755
Wasserstein Gradient Flow over Variational Parameter Space for Variational Inference
Dai Hai Nguyen, Tetsuya Sakurai, Hiroshi Mamitsuka; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1756-1764
On Tractability of Learning Bayesian Networks with Ancestral Constraints
Juha Harviainen, Pekka Parviainen; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1765-1773
High-probability Convergence Bounds for Online Nonlinear Stochastic Gradient Descent under Heavy-tailed Noise
Aleksandar Armacki, Shuhua Yu, Pranay Sharma, Gauri Joshi, Dragana Bajovic, Dusan Jakovetic, Soummya Kar; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1774-1782
Hyperboloid GPLVM for Discovering Continuous Hierarchies via Nonparametric Estimation
Koshi Watanabe, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1783-1791
From Learning to Optimize to Learning Optimization Algorithms
Camille Castera, Peter Ochs; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1792-1800
Factor Analysis with Correlated Topic Model for Multi-Modal Data
Małgorzata Łazęcka, Ewa Maria Szczurek; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1801-1809
Pure Exploration with Feedback Graphs
Alessio Russo, Yichen Song, Aldo Pacchiano; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1810-1818
The Hardness of Validating Observational Studies with Experimental Data
Jake Fawkes, Michael O’Riordan, Athanasios Vlontzos, Oriol Corcoll, Ciarán Mark Gilligan-Lee; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1819-1827
Learning Graph Node Embeddings by Smooth Pair Sampling
Konstantin Kutzkov; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1828-1836
Personalized Convolutional Dictionary Learning of Physiological Time Series
Axel Roques, Samuel Gruffaz, Kyurae Kim, Alain Oliviero Durmus, Laurent Oudre; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1837-1845
Approximating the Total Variation Distance between Gaussians
Arnab Bhattacharyya, Weiming Feng, Piyush Srivastava; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1846-1854
Performative Prediction on Games and Mechanism Design
António Góis, Mehrnaz Mofakhami, Fernando P. Santos, Gauthier Gidel, Simon Lacoste-Julien; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1855-1863
A Multi-Armed Bandit Approach to Online Selection and Evaluation of Generative Models
Xiaoyan Hu, Ho-fung Leung, Farzan Farnia; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1864-1872
Partial Information Decomposition for Data Interpretability and Feature Selection
Charles Westphal, Stephen Hailes, Mirco Musolesi; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1873-1881
Energy-consistent Neural Operators for Hamiltonian and Dissipative Partial Differential Equations
Yusuke Tanaka, Takaharu Yaguchi, Tomoharu Iwata, Naonori Ueda; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1882-1890
On the Difficulty of Constructing a Robust and Publicly-Detectable Watermark
Jaiden Fairoze, Guillermo Ortiz-Jimenez, Mel Vecerik, Somesh Jha, Sven Gowal; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1891-1899
Hierarchical Bias-Driven Stratification for Interpretable Causal Effect Estimation
Lucile Ter-Minassian, Liran Szlak, Ehud Karavani, Christopher C. Holmes, Yishai Shimoni; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1900-1908
Model Evaluation in the Dark: Robust Classifier Metrics with Missing Labels
Danial Dervovic, Michael Cashmore; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1909-1917
RetroDiff: Retrosynthesis as Multi-stage Distribution Interpolation
Yiming Wang, Yuxuan Song, Yiqun Wang, Minkai Xu, Rui Wang, Hao Zhou, Wei-Ying Ma; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1918-1926
QuACK: A Multipurpose Queuing Algorithm for Cooperative $k$-Armed Bandits
Benjamin Howson, Sarah Lucie Filippi, Ciara Pike-Burke; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1927-1935
Changepoint Estimation in Sparse Dynamic Stochastic Block Models under Near-Optimal Signal Strength
Shirshendu Chatterjee, Soumendu Sundar Mukherjee, TAMOJIT SADHUKHAN; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1936-1944
Multi-Agent Credit Assignment with Pretrained Language Models
Wenhao Li, Dan Qiao, Baoxiang Wang, Xiangfeng Wang, Wei Yin, Hao Shen, Bo Jin, Hongyuan Zha; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1945-1953
Contractivity and linear convergence in bilinear saddle-point problems: An operator-theoretic approach
Colin Dirren, Mattia Bianchi, Panagiotis D. Grontas, John Lygeros, Florian Dorfler; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1954-1962
Change Point Detection in Hadamard Spaces by Alternating Minimization
Anica Kostic, Vincent Runge, Charles Truong; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1963-1971
TempTest: Local Normalization Distortion and the Detection of Machine-generated Text
Tom Kempton, Stuart Burrell, Connor J Cheverall; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1972-1980
StableMDS: A Novel Gradient Descent-Based Method for Stabilizing and Accelerating Weighted Multidimensional Scaling
Zhongxi Fang, Xun Su, Tomohisa Tabuchi, Jianming Huang, Hiroyuki Kasai; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1981-1989
Differentially Private Continual Release of Histograms and Related Queries
Monika Henzinger, A. R. Sricharan, Teresa Anna Steiner; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1990-1998
Implicit Diffusion: Efficient optimization through stochastic sampling
Pierre Marion, Anna Korba, Peter Bartlett, Mathieu Blondel, Valentin De Bortoli, Arnaud Doucet, Felipe Llinares-López, Courtney Paquette, Quentin Berthet; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:1999-2007
Information-Theoretic Causal Discovery in Topological Order
Sascha Xu, Sarah Mameche, Jilles Vreeken; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2008-2016
A Unified Evaluation Framework for Epistemic Predictions
Shireen Kudukkil Manchingal, Muhammad Mubashar, Kaizheng Wang, Fabio Cuzzolin; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2017-2025
LMEraser: Large Model Unlearning via Adaptive Prompt Tuning
Jie Xu, Zihan Wu, Cong Wang, Xiaohua Jia; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2026-2034
All models are wrong, some are useful: Model Selection with Limited Labels
Patrik Okanovic, Andreas Kirsch, Jannes Kasper, Torsten Hoefler, Andreas Krause, Nezihe Merve Gürel; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2035-2043
Active Bipartite Ranking with Smooth Posterior Distributions
James Cheshire, Stephan Clémençon; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2044-2052
The Sample Complexity of Stackelberg Games
Francesco Bacchiocchi, Matteo Bollini, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2053-2061
Bayes without Underfitting: Fully Correlated Deep Learning Posteriors via Alternating Projections
Marco Miani, Hrittik Roy, Søren Hauberg; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2062-2070
Computation-Aware Kalman Filtering and Smoothing
Marvin Pförtner, Jonathan Wenger, Jon Cockayne, Philipp Hennig; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2071-2079
Robust Gradient Descent for Phase Retrieval
Alex Buna, Patrick Rebeschini; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2080-2088
Distribution-Aware Mean Estimation under User-level Local Differential Privacy
Corentin Pla, Maxime Vono, Hugo Richard; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2089-2097
Calibrated Computation-Aware Gaussian Processes
Disha Hegde, Mohamed Adil, Jon Cockayne; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2098-2106
Towards Fair Graph Learning without Demographic Information
Zichong Wang, Nhat Hoang, Xingyu Zhang, Kevin Bello, Xiangliang Zhang, Sundararaja Sitharama Iyengar, Wenbin Zhang; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2107-2115
Data-Driven Upper Confidence Bounds with Near-Optimal Regret for Heavy-Tailed Bandits
Ambrus Tamás, Szabolcs Szentpéteri, Balázs Csáji; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2116-2124
Gaussian Smoothing in Saliency Maps: The Stability-Fidelity Trade-Off in Neural Network Interpretability
Zhuorui Ye, Farzan Farnia; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2125-2133
Disentangling Interactions and Dependencies in Feature Attributions
Gunnar König, Eric Günther, Ulrike von Luxburg; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2134-2142
A Causal Framework for Evaluating Deferring Systems
Filippo Palomba, Andrea Pugnana, Jose Manuel Alvarez, Salvatore Ruggieri; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2143-2151
Generalization Bounds for Dependent Data using Online-to-Batch Conversion.
Sagnik Chatterjee, MANUJ MUKHERJEE, Alhad Sethi; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2152-2160
Tensor Network-Constrained Kernel Machines as Gaussian Processes
Frederiek Wesel, Kim Batselier; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2161-2169
Accuracy on the wrong line: On the pitfalls of noisy data for out-of-distribution generalisation
Amartya Sanyal, Yaxi Hu, Yaodong Yu, Yian Ma, Yixin Wang, Bernhard Schölkopf; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2170-2178
Classification of High-dimensional Time Series in Spectral Domain Using Explainable Features with Applications to Neuroimaging Data
Sarbojit Roy, Malik Shahid Sultan, Tania Reyes Vallejo, Leena Ali Ibrahim, Hernando Ombao; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2179-2187
Incremental Uncertainty-aware Performance Monitoring with Active Labeling Intervention
Alexander Koebler, Thomas Decker, Ingo Thon, Volker Tresp, Florian Buettner; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2188-2196
Legitimate ground-truth-free metrics for deep uncertainty classification scoring
Arthur Pignet, Chiara Regniez, John Klein; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2197-2205
Information-Theoretic Measures on Lattices for Higher-Order Interactions
Zhaolu Liu, Mauricio Barahona, Robert Peach; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2206-2214
Common Learning Constraints Alter Interpretations of Direct Preference Optimization
Lemin Kong, Xiangkun Hu, Tong He, David Wipf; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2215-2223
A Random Matrix Theory Perspective on the Spectrum of Learned Features and Asymptotic Generalization Capabilities
Yatin Dandi, Luca Pesce, Hugo Cui, Florent Krzakala, Yue Lu, Bruno Loureiro; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2224-2232
Best-Arm Identification in Unimodal Bandits
Riccardo Poiani, Marc Jourdan, Emilie Kaufmann, Rémy Degenne; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2233-2241
ChronosX: Adapting Pretrained Time Series Models with Exogenous Variables
Sebastian Pineda Arango, Pedro Mercado, Shubham Kapoor, Abdul Fatir Ansari, Lorenzo Stella, Huibin Shen, Hugo Henri Joseph Senetaire, Ali Caner Turkmen, Oleksandr Shchur, Danielle C. Maddix, Michael Bohlke-Schneider, Bernie Wang, Syama Sundar Rangapuram; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2242-2250
Reward Maximization for Pure Exploration: Minimax Optimal Good Arm Identification for Nonparametric Multi-Armed Bandits
Brian M Cho, Dominik Meier, Kyra Gan, Nathan Kallus; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2251-2259
Efficient Trajectory Inference in Wasserstein Space Using Consecutive Averaging
Amartya Banerjee, Harlin Lee, Nir Sharon, Caroline Moosmüller; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2260-2268
Efficient Exploitation of Hierarchical Structure in Sparse Reward Reinforcement Learning
Gianluca Drappo, Arnaud Robert, Marcello Restelli, Aldo A. Faisal, Alberto Maria Metelli, Ciara Pike-Burke; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2269-2277
Distributional Adversarial Loss
Saba Ahmadi, Siddharth Bhandari, Avrim Blum, Chen Dan, Prabhav Jain; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2278-2286
A Subquadratic Time Approximation Algorithm for Individually Fair k-Center
Matthijs Ebbens, Nicole Funk, Jan Höckendorff, Christian Sohler, Vera Weil; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2287-2295
Global Optimization of Gaussian Process Acquisition Functions Using a Piecewise-Linear Kernel Approximation
Yilin Xie, Shiqiang Zhang, Joel Paulson, Calvin Tsay; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2296-2304
Credibility-Aware Multimodal Fusion Using Probabilistic Circuits
Sahil Sidheekh, Pranuthi Tenali, Saurabh Mathur, Erik Blasch, Kristian Kersting, Sriraam Natarajan; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2305-2313
Learning from biased positive-unlabeled data via threshold calibration
Paweł Teisseyre, Timo Martens, Jessa Bekker, Jesse Davis; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2314-2322
Near-Polynomially Competitive Active Logistic Regression
Yihan Zhou, Eric Price, Trung Nguyen; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2323-2331
DeCaf: A Causal Decoupling Framework for OOD Generalization on Node Classification
Xiaoxue Han, Huzefa Rangwala, Yue Ning; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2332-2340
Fair Resource Allocation in Weakly Coupled Markov Decision Processes
Xiaohui Tu, Yossiri Adulyasak, Nima Akbarzadeh, Erick Delage; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2341-2349
Robust Fair Clustering with Group Membership Uncertainty Sets
Sharmila Duppala, Juan Luque, John P Dickerson, Seyed A. Esmaeili; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2350-2358
FLIPHAT: Joint Differential Privacy for High Dimensional Linear Bandits
Saptarshi Roy, Sunrit Chakraborty, Debabrota Basu; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2359-2367
When the Universe is Too Big: Bounding Consideration Probabilities for Plackett-Luce Rankings
Ben Aoki-Sherwood, Catherine Bregou, David Liben-Nowell, Kiran Tomlinson, Thomas Zeng; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2368-2376
Conditional diffusions for amortized neural posterior estimation
Tianyu Chen, Vansh Bansal, James G. Scott; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2377-2385
On adaptivity and minimax optimality of two-sided nearest neighbors
Tathagata Sadhukhan, Manit Paul, Raaz Dwivedi; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2386-2394
Decision from Suboptimal Classifiers: Excess Risk Pre- and Post-Calibration
Alexandre Perez-Lebel, Gael Varoquaux, Sanmi Koyejo, Matthieu Doutreligne, Marine Le Morvan; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2395-2403
Statistical Guarantees for Unpaired Image-to-Image Cross-Domain Analysis using GANs
Saptarshi Chakraborty, Peter Bartlett; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2404-2412
From Gradient Clipping to Normalization for Heavy Tailed SGD
Florian Hübler, Ilyas Fatkhullin, Niao He; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2413-2421
Deep Optimal Sensor Placement for Black Box Stochastic Simulations
Paula Cordero Encinar, Tobias Schröder, Peter Yatsyshin, Andrew B. Duncan; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2422-2430
Adversarially-Robust TD Learning with Markovian Data: Finite-Time Rates and Fundamental Limits
Sreejeet Maity, Aritra Mitra; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2431-2439
Explaining ViTs Using Information Flow
Chase Walker, Md Rubel Ahmed, Sumit Kumar Jha, Rickard Ewetz; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2440-2448
Zero-Shot Action Generalization with Limited Observations
Abdullah Alchihabi, Hanping Zhang, Yuhong Guo; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2449-2457
Conditional Prediction ROC Bands for Graph Classification
Yujia Wu, Bo Yang, Elynn Chen, Yuzhou Chen, Zheshi Zheng; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2458-2466
Fundamental computational limits of weak learnability in high-dimensional multi-index models
Emanuele Troiani, Yatin Dandi, Leonardo Defilippis, Lenka Zdeborova, Bruno Loureiro, Florent Krzakala; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2467-2475
MDP Geometry, Normalization and Reward Balancing Solvers
Arsenii Mustafin, Aleksei Pakharev, Alex Olshevsky, Ioannis Paschalidis; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2476-2484
BudgetIV: Optimal Partial Identification of Causal Effects with Mostly Invalid Instruments
Jordan Penn, Lee M. Gunderson, Gecia Bravo-Hermsdorff, Ricardo Silva, David Watson; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2485-2493
Variation Due to Regularization Tractably Recovers Bayesian Deep Learning Uncertainty
James McInerney, Nathan Kallus; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2494-2502
Variance-Dependent Regret Bounds for Nonstationary Linear Bandits
Zhiyong Wang, Jize Xie, Yi Chen, John C.S. Lui, Dongruo Zhou; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2503-2511
Spectral Differential Network Analysis for High-Dimensional Time Series
Michael Hellstern, Byol Kim, Zaid Harchaoui, Ali Shojaie; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2512-2520
Time-series attribution maps with regularized contrastive learning
Steffen Schneider, Rodrigo González Laiz, Anastasiia Filippova, Markus Frey, Mackenzie W Mathis; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2521-2529
A High Dimensional Statistical Model for Adversarial Training: Geometry and Trade-Offs
Kasimir Tanner, Matteo Vilucchio, Bruno Loureiro, Florent Krzakala; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2530-2538
Revisiting LocalSGD and SCAFFOLD: Improved Rates and Missing Analysis
Ruichen Luo, Sebastian U Stich, Samuel Horváth, Martin Takáč; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2539-2547
An Iterative Algorithm for Rescaled Hyperbolic Functions Regression
Yeqi Gao, Zhao Song, Junze Yin; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2548-2556
Analyzing the Role of Permutation Invariance in Linear Mode Connectivity
Keyao Zhan, Puheng Li, Lei Wu; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2557-2565
Restructuring Tractable Probabilistic Circuits
Honghua Zhang, Benjie Wang, Marcelo Arenas, Guy Van den Broeck; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2566-2574
Asynchronous Decentralized Optimization with Constraints: Achievable Speeds of Convergence for Directed Graphs
Firooz Shahriari-Mehr, Ashkan Panahi; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2575-2583
Synthesis and Analysis of Data as Probability Measures With Entropy-Regularized Optimal Transport
Brendan Mallery, James M. Murphy, Shuchin Aeron; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2584-2592
Sampling From Multiscale Densities With Delayed Rejection Generalized Hamiltonian Monte Carlo
Gilad Turok, Chirag Modi, Bob Carpenter; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2593-2601
Differentially Private Graph Data Release: Inefficiencies & Unfairness
Ferdinando Fioretto, Diptangshu Sen, Juba Ziani; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2602-2610
Improving N-Glycosylation and Biopharmaceutical Production Predictions Using AutoML-Built Residual Hybrid Models
Pedro Seber, Richard Braatz; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2611-2619
Parabolic Continual Learning
Haoming Yang, Ali Hasan, Vahid Tarokh; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2620-2628
Robust Kernel Hypothesis Testing under Data Corruption
Antonin Schrab, Ilmun Kim; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2629-2637
A Multi-Task Learning Approach to Linear Multivariate Forecasting
Liran Nochumsohn, Hedi Zisling, Omri Azencot; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2638-2646
Looped ReLU MLPs May Be All You Need as Practical Programmable Computers
Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song, Yufa Zhou; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2647-2655
Pick-to-Learn and Self-Certified Gaussian Process Approximations
Daniel Marks, Dario Paccagnan; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2656-2664
Q-learning for Quantile MDPs: A Decomposition, Performance, and Convergence Analysis
Jia Lin Hau, Erick Delage, Esther Derman, Mohammad Ghavamzadeh, Marek Petrik; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2665-2673
Sparse Activations as Conformal Predictors
Margarida M Campos, João Cálem, Sophia Sklaviadis, Mario A. T. Figueiredo, Andre Martins; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2674-2682
Robust Multi-fidelity Bayesian Optimization with Deep Kernel and Partition
Fengxue Zhang, Thomas Desautels, Yuxin Chen; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2683-2691
Is Prior-Free Black-Box Non-Stationary Reinforcement Learning Feasible?
Argyrios Gerogiannis, Yu-Han Huang, Venugopal Veeravalli; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2692-2700
Your Finetuned Large Language Model is Already a Powerful Out-of-distribution Detector
Andi Zhang, Tim Z. Xiao, Weiyang Liu, Robert Bamler, Damon Wischik; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2701-2709
When Can We Solve the Weighted Low Rank Approximation Problem in Truly Subquadratic Time?
Chenyang Li, Yingyu Liang, Zhenmei Shi, Zhao Song; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2710-2718
Spectral Representation for Causal Estimation with Hidden Confounders
Haotian Sun, Antoine Moulin, Tongzheng Ren, Arthur Gretton, Bo Dai; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2719-2727
Geometric Collaborative Filtering with Convergence
Hisham Husain, Julien Monteil; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2728-2736
Learning Infinite-Horizon Average-Reward Linear Mixture MDPs of Bounded Span
Woojin Chae, Kihyuk Hong, Yufan Zhang, Ambuj Tewari, Dabeen Lee; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2737-2745
Flexible and Efficient Probabilistic PDE Solvers through Gaussian Markov Random Fields
Tim Weiland, Marvin Pförtner, Philipp Hennig; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2746-2754
Learning Laplacian Positional Encodings for Heterophilous Graphs
Michael Ito, Jiong Zhu, Dexiong Chen, Danai Koutra, Jenna Wiens; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2755-2763
Understanding GNNs and Homophily in Dynamic Node Classification
Michael Ito, Danai Koutra, Jenna Wiens; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2764-2772
Causal Discovery on Dependent Binary Data
Alex Chen, Qing Zhou; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2773-2781
A Safe Bayesian Learning Algorithm for Constrained MDPs with Bounded Constraint Violation
Krishna C Kalagarla, Rahul Jain, Pierluigi Nuzzo; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2782-2790
Statistical Learning of Distributionally Robust Stochastic Control in Continuous State Spaces
Shengbo Wang, Nian Si, Jose Blanchet, Zhengyuan Zhou; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2791-2799
Calm Composite Losses: Being Improper Yet Proper Composite
Han Bao, Nontawat Charoenphakdee; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2800-2808
Optimistic Safety for Online Convex Optimization with Unknown Linear Constraints
Spencer Hutchinson, Tianyi Chen, Mahnoosh Alizadeh; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2809-2817
Approximate Global Convergence of Independent Learning in Multi-Agent Systems
Ruiyang Jin, Zaiwei Chen, Yiheng Lin, Jie Song, Adam Wierman; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2818-2826
Protein Fitness Landscape: Spectral Graph Theory Perspective
Hao Zhu, Daniel M. Steinberg, Piotr Koniusz; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2827-2835
A Tight Regret Analysis of Non-Parametric Repeated Contextual Brokerage
François Bachoc, Tommaso Cesari, Roberto Colomboni; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2836-2844
Evidential Uncertainty Probes for Graph Neural Networks
Linlin Yu, Kangshuo Li, Pritom Kumar Saha, Yifei Lou, Feng Chen; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2845-2853
Quantifying the Optimization and Generalization Advantages of Graph Neural Networks Over Multilayer Perceptrons
Wei Huang, Yuan Cao, Haonan Wang, Xin Cao, Taiji Suzuki; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2854-2862
Memory-Efficient Optimization with Factorized Hamiltonian Descent
Son Nguyen, Lizhang Chen, Bo Liu, Qiang Liu; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2863-2871
Computing high-dimensional optimal transport by flow neural networks
Chen Xu, Xiuyuan Cheng, Yao Xie; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2872-2880
Is Gibbs sampling faster than Hamiltonian Monte Carlo on GLMs?
Son Luu, Zuheng Xu, Nikola Surjanovic, Miguel Biron-Lattes, Trevor Campbell, Alexandre Bouchard-Cote; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2881-2889
On Preference-based Stochastic Linear Contextual Bandits with Knapsacks
Xin Liu; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2890-2898
Decoupling epistemic and aleatoric uncertainties with possibility theory
Nong Minh Hieu, Jeremie Houssineau, Neil K. Chada, Emmanuel Delande; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2899-2907
Permutation Invariant Functions: Statistical Testing, Density Estimation, and Metric Entropy
Wee Chaimanowong, Ying Zhu; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2908-2916
Recurrent Neural Goodness-of-Fit Test for Time Series
Aoran Zhang, Wenbin Zhou, Liyan Xie, Shixiang Zhu; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2917-2925
Transfer Learning for High-dimensional Reduced Rank Time Series Models
Mingliang Ma, Abolfazl Safikhani; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2926-2934
Decision-Point Guided Safe Policy Improvement
Abhishek Sharma, Leo Benac, Sonali Parbhoo, Finale Doshi-Velez; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2935-2943
Understanding Inverse Reinforcement Learning under Overparameterization: Non-Asymptotic Analysis and Global Optimality
Ruijia Zhang, Siliang Zeng, Chenliang Li, Alfredo Garcia, Mingyi Hong; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2944-2952
New User Event Prediction Through the Lens of Causal Inference
Henry Yuchi, Shixiang Zhu, Li Dong, Yigit M. Arisoy, Matthew C. Spencer; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2953-2961
Variational Combinatorial Sequential Monte Carlo for Bayesian Phylogenetics in Hyperbolic Space
Alex Chen, Philippe Chlenski, Kenneth Munyuza, Antonio Khalil Moretti, Christian A. Naesseth, Itsik Pe’er; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2962-2970
Multi-level Advantage Credit Assignment for Cooperative Multi-Agent Reinforcement Learning
Xutong Zhao, Yaqi Xie; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2971-2979
Sampling in High-Dimensions using Stochastic Interpolants and Forward-Backward Stochastic Differential Equations
Anand Jerry George, Nicolas Macris; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2980-2988
Reinforcement Learning for Infinite-Horizon Average-Reward Linear MDPs via Approximation by Discounted-Reward MDPs
Kihyuk Hong, Woojin Chae, Yufan Zhang, Dabeen Lee, Ambuj Tewari; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2989-2997
Functional Stochastic Gradient MCMC for Bayesian Neural Networks
Mengjing Wu, Junyu Xuan, Jie Lu; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:2998-3006
Meta-learning from Heterogeneous Tensors for Few-shot Tensor Completion
Tomoharu Iwata, Atsutoshi Kumagai; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3007-3015
HR-Bandit: Human-AI Collaborated Linear Recourse Bandit
Junyu Cao, Ruijiang Gao, Esmaeil Keyvanshokooh; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3016-3024
ADEPT: Hierarchical Bayes Approach to Personalized Federated Unsupervised Learning
Kaan Ozkara, Bruce Huang, Ruida Zhou, Suhas Diggavi; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3025-3033
Domain Adaptation and Entanglement: an Optimal Transport Perspective
Okan Koc, Alexander Soen, Chao-Kai Chiang, Masashi Sugiyama; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3034-3042
Invertible Fourier Neural Operators for Tackling Both Forward and Inverse Problems
Da Long, Zhitong Xu, Qiwei Yuan, Yin Yang, Shandian Zhe; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3043-3051
Meta-learning Task-specific Regularization Weights for Few-shot Linear Regression
Tomoharu Iwata, Atsutoshi Kumagai, Yasutoshi Ida; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3052-3060
Subspace Recovery in Winsorized PCA: Insights into Accuracy and Robustness
Sangil Han, Kyoowon Kim, Sungkyu Jung; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3061-3069
Stochastic Gradient Descent for Bézier Simplex Representation of Pareto Set in Multi-Objective Optimization
Yasunari Hikima, Ken Kobayashi, Akinori Tanaka, Akiyoshi Sannai, Naoki Hamada; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3070-3078
HACSurv: A Hierarchical Copula-Based Approach for Survival Analysis with Dependent Competing Risks
Xin Liu, Weijia Zhang, Min-Ling Zhang; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3079-3087
Causal discovery in mixed additive noise models
Ruicong Yao, Tim Verdonck, Jakob Raymaekers; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3088-3096
Riemann$^2$: Learning Riemannian Submanifolds from Riemannian Data
Leonel Rozo, Miguel González-Duque, Noémie Jaquier, Søren Hauberg; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3097-3105
High Dimensional Bayesian Optimization using Lasso Variable Selection
Vu Viet Hoang, Hung The Tran, Sunil Gupta, Vu Nguyen; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3106-3114
Differentiable Causal Structure Learning with Identifiability by NOTIME
Jeroen Berrevoets, Jakob Raymaekers, Mihaela van der Schaar, Tim Verdonck, Ruicong Yao; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3115-3123
Out-of-distribution robustness for multivariate analysis via causal regularisation
Homer Durand, Gherardo Varando, Nathan Mankovich, Gustau Camps-Valls; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3124-3132
Memorization in Attention-only Transformers
Léo Dana, Muni Sreenivas Pydi, Yann Chevaleyre; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3133-3141
Multimodal Learning with Uncertainty Quantification based on Discounted Belief Fusion
Grigor Bezirganyan, Sana Sellami, Laure Berti-Equille, Sébastien Fournier; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3142-3150
Koopman-Equivariant Gaussian Processes
Petar Bevanda, Max Beier, Alexandre Capone, Stefan Georg Sosnowski, Sandra Hirche, Armin Lederer; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3151-3159
Continuous Structure Constraint Integration for Robust Causal Discovery
Lyuzhou Chen, Taiyu Ban, Derui Lyu, Yijia Sun, Kangtao Hu, Xiangyu Wang, Huanhuan Chen; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3160-3168
Infinite Width Limits of Self Supervised Neural Networks
Maximilian Fleissner, Gautham Govind Anil, Debarghya Ghoshdastidar; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3169-3177
Safety in the Face of Adversity: Achieving Zero Constraint Violation in Online Learning with Slowly Changing Constraints
Bassel Hamoud, Ilnura Usmanova, Kfir Yehuda Levy; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3178-3186
What Ails Generative Structure-based Drug Design: Expressivity is Too Little or Too Much?
Rafal Karczewski, Samuel Kaski, Markus Heinonen, Vikas K Garg; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3187-3195
TRADE: Transfer of Distributions between External Conditions with Normalizing Flows
Stefan Wahl, Armand Rousselot, Felix Draxler, Ullrich Koethe; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3196-3204
Sketch-and-Project Meets Newton Method: Global $O(1/k^2)$ Convergence with Low-Rank Updates
Slavomir Hanzely; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3205-3213
Statistical Test for Auto Feature Engineering by Selective Inference
Tatsuya Matsukawa, Tomohiro Shiraishi, Shuichi Nishino, Teruyuki Katsuoka, Ichiro Takeuchi; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3214-3222
Differential Privacy in Distributed Learning: Beyond Uniformly Bounded Stochastic Gradients
Yue Huang, Jiaojiao Zhang, Qing Ling; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3223-3231
Performative Reinforcement Learning with Linear Markov Decision Process
Debmalya Mandal, Goran Radanovic; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3232-3240
On the Identifiability of Causal Abstractions
Xiusi Li, Sékou-Oumar Kaba, Siamak Ravanbakhsh; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3241-3249
Powerful batch conformal prediction for classification
Ulysse Gazin, Ruth Heller, Etienne Roquain, Aldo Solari; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3250-3258
Composition and Control with Distilled Energy Diffusion Models and Sequential Monte Carlo
James Thornton, Louis Béthune, Ruixiang ZHANG, Arwen Bradley, Preetum Nakkiran, Shuangfei Zhai; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3259-3267
Fixed-Budget Change Point Identification in Piecewise Constant Bandits
Joseph Lazzaro, Ciara Pike-Burke; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3268-3276
Tensor Network Based Feature Learning Model
Albert Saiapin, Kim Batselier; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3277-3285
Sample Compression Unleashed: New Generalization Bounds for Real Valued Losses
Mathieu Bazinet, Valentina Zantedeschi, Pascal Germain; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3286-3294
Global Ground Metric Learning with Applications to scRNA data
Damin Kühn, Michael T Schaub; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3295-3303
Independent Learning in Performative Markov Potential Games
Rilind Sahitaj, Paulius Sasnauskas, Yiğit Yalın, Debmalya Mandal, Goran Radanovic; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3304-3312
Parallel Backpropagation for Inverse of a Convolution with Application to Normalizing Flows
Sandeep Nagar, Girish Varma; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3313-3321
A Differential Inclusion Approach for Learning Heterogeneous Sparsity in Neuroimaging Analysis
Wenjing Han, Yueming Wu, Xinwei Sun, Lingjing Hu, Yizhou Wang; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3322-3330
Narrowing the Gap between Adversarial and Stochastic MDPs via Policy Optimization
Daniil Tiapkin, Evgenii Chzhen, Gilles Stoltz; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3331-3339
SNAP: Sequential Non-Ancestor Pruning for Targeted Causal Effect Estimation With an Unknown Graph
Mátyás Schubert, Tom Claassen, Sara Magliacane; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3340-3348
Do Regularization Methods for Shortcut Mitigation Work As Intended?
Haoyang Hong, Ioanna Papanikolaou, Sonali Parbhoo; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3349-3357
Hyperbolic Prototypical Entailment Cones for Image Classification
Samuele Fonio, Roberto Esposito, Marco Aldinucci; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3358-3366
Information Transfer Across Clinical Tasks via Adaptive Parameter Optimisation
Anshul Thakur, Elena Gal, Soheila Molaei, Xiao Gu, Patrick Schwab, Danielle Belgrave, Kim Branson, David A. Clifton; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3367-3375
Online-to-PAC generalization bounds under graph-mixing dependencies
Baptiste Abélès, Gergely Neu, Eugenio Clerico; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3376-3384
Covariance Selection over Networks
Wenfu Xia, Fengpei Li, Ying Sun, Ziping Zhao; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3385-3393
Sparse Causal Effect Estimation using Two-Sample Summary Statistics in the Presence of Unmeasured Confounding
Shimeng Huang, Niklas Pfister, Jack Bowden; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3394-3402
Vecchia Gaussian Process Ensembles on Internal Representations of Deep Neural Networks
Felix Jimenez, Matthias Katzfuss; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3403-3411
Separation-Based Distance Measures for Causal Graphs
Jonas Wahl, Jakob Runge; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3412-3420
Order-Optimal Regret with Novel Policy Gradient Approaches in Infinite-Horizon Average Reward MDPs
Swetha Ganesh, Washim Uddin Mondal, Vaneet Aggarwal; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3421-3429
FreqMoE: Enhancing Time Series Forecasting through Frequency Decomposition Mixture of Experts
Ziqi Liu; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3430-3438
Enhanced Adaptive Gradient Algorithms for Nonconvex-PL Minimax Optimization
Feihu Huang, Chunyu Xuan, Xinrui Wang, Siqi Zhang, Songcan Chen; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3439-3447
Federated Causal Inference: Multi-Study ATE Estimation beyond Meta-Analysis
Rémi Khellaf, Aurélien Bellet, Julie Josse; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3448-3456
Optimal Time Complexity Algorithms for Computing General Random Walk Graph Kernels on Sparse Graphs
Krzysztof Marcin Choromanski, Isaac Reid, Arijit Sehanobish, Kumar Avinava Dubey; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3457-3465
Variational Inference in Location-Scale Families: Exact Recovery of the Mean and Correlation Matrix
Charles Margossian, Lawrence K. Saul; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3466-3474
A Theoretical Understanding of Chain-of-Thought: Coherent Reasoning and Error-Aware Demonstration
Yingqian Cui, Pengfei He, Xianfeng Tang, Qi He, Chen Luo, Jiliang Tang, Yue Xing; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3475-3483
A graphical global optimization framework for parameter estimation of statistical models with nonconvex regularization functions
Danial Davarnia, Mohammadreza Kiaghadi; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3484-3492
High-Dimensional Differential Parameter Inference in Exponential Family using Time Score Matching
Daniel James Williams, Leyang Wang, Qizhen Ying, Song Liu, Mladen Kolar; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3493-3501
Large Covariance Matrix Estimation With Nonnegative Correlations
Yixin Yan, QIAO YANG, Ziping Zhao; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3502-3510
TVineSynth: A Truncated C-Vine Copula Generator of Synthetic Tabular Data to Balance Privacy and Utility
Elisabeth Griesbauer, Claudia Czado, Arnoldo Frigessi, Ingrid Hobæk Haff; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3511-3519
Fairness Risks for Group-Conditionally Missing Demographics
Kaiqi Jiang, Wenzhe Fan, Mao Li, Xinhua Zhang; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3520-3528
Anytime-Valid A/B Testing of Counting Processes
Michael Lindon, Nathan Kallus; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3529-3537
Diffusion Models under Group Transformations
Haoye Lu, Spencer Szabados, Yaoliang Yu; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3538-3546
Theoretical Convergence Guarantees for Variational Autoencoders
Sobihan Surendran, Antoine Godichon-Baggioni, Sylvain Le Corff; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3547-3555
Infinite-dimensional Diffusion Bridge Simulation via Operator Learning
Gefan Yang, Elizabeth Louise Baker, Michael Lind Severinsen, Christy Anna Hipsley, Stefan Sommer; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3556-3564
Natural Language Counterfactual Explanations for Graphs Using Large Language Models
Flavio Giorgi, Cesare Campagnano, Fabrizio Silvestri, Gabriele Tolomei; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3565-3573
Nonparametric estimation of Hawkes processes with RKHSs
Anna Bonnet, Maxime Sangnier; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3574-3582
Rethinking Neural-based Matrix Inversion: Why can’t, and Where can
Yuliang Ji, Jian Wu, Yuanzhe Xi; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3583-3591
A Safe Exploration Approach to Constrained Markov Decision Processes
Tingting Ni, Maryam Kamgarpour; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3592-3600
Towards Cost Sensitive Decision Making
Yang Li, Junier Oliva; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3601-3609
Weighted Sum of Gaussian Process Latent Variable Models
James A C Odgers, Ruby Sedgwick, Chrysoula Dimitra Kappatou, Ruth Misener, Sarah Lucie Filippi; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3610-3618
Survival Models: Proper Scoring Rule and Stochastic Optimization with Competing Risks
Julie Alberge, Vincent Maladiere, Olivier Grisel, Judith Abécassis, Gael Varoquaux; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3619-3627
Density-Dependent Group Testing
Rahil Morjaria, Saikiran Bulusu, Venkata Gandikota, Sidharth Jaggi; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3628-3636
Offline RL via Feature-Occupancy Gradient Ascent
Gergely Neu, Nneka Okolo; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3637-3645
Gated Recurrent Neural Networks with Weighted Time-Delay Feedback
N. Benjamin Erichson, Soon Hoe Lim, Michael W. Mahoney; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3646-3654
LC-Tsallis-INF: Generalized Best-of-Both-Worlds Linear Contextual Bandits
Masahiro Kato, Shinji Ito; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3655-3663
Theoretically Grounded Pruning of Large Ground Sets for Constrained, Discrete Optimization
Ankur Nath, Alan Kuhnle; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3664-3672
A Novel Convex Gaussian Min Max Theorem for Repeated Features
David Bosch, Ashkan Panahi; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3673-3681
Unveiling the Role of Randomization in Multiclass Adversarial Classification: Insights from Graph Theory
Lucas Gnecco Heredia, Matteo Sammut, Muni Sreenivas Pydi, Rafael Pinot, Benjamin Negrevergne, Yann Chevaleyre; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3682-3690
On the Computational Tractability of the (Many) Shapley Values
Reda Marzouk, Shahaf Bassan, Guy Katz, De la Higuera; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3691-3699
Causal Representation Learning from General Environments under Nonparametric Mixing
Ignavier Ng, Shaoan Xie, Xinshuai Dong, Peter Spirtes, Kun Zhang; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3700-3708
Conditioning diffusion models by explicit forward-backward bridging
Adrien Corenflos, Zheng Zhao, Thomas B. Schön, Simo Särkkä, Jens Sjölund; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3709-3717
Stochastic Approximation with Unbounded Markovian Noise: A General-Purpose Theorem
Shaan Ul Haque, Siva Theja Maguluri; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3718-3726
Learning Visual-Semantic Subspace Representations
Gabriel Moreira, Manuel Marques, Joao Costeira, Alexander G Hauptmann; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3727-3735
Kernel Single Proxy Control for Deterministic Confounding
Liyuan Xu, Arthur Gretton; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3736-3744
Copula Based Trainable Calibration Error Estimator of Multi-Label Classification with Label Interdependencies
Arkapal Panda, Utpal Garain; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3745-3753
Causal Discovery-Driven Change Point Detection in Time Series
Shanyun Gao, Raghavendra Addanki, Tong Yu, Ryan A. Rossi, Murat Kocaoglu; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3754-3762
Scalable Out-of-Distribution Robustness in the Presence of Unobserved Confounders
Parjanya Prajakta Prashant, Seyedeh Baharan Khatami, Bruno Ribeiro, Babak Salimi; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3763-3771
SemlaFlow – Efficient 3D Molecular Generation with Latent Attention and Equivariant Flow Matching
Ross Irwin, Alessandro Tibo, Jon Paul Janet, Simon Olsson; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3772-3780
Two-Timescale Linear Stochastic Approximation: Constant Stepsizes Go a Long Way
Jeongyeol Kwon, Luke Dotson, Yudong Chen, Qiaomin Xie; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3781-3789
Your copula is a classifier in disguise: classification-based copula density estimation
David Huk, Mark Steel, Ritabrata Dutta; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3790-3798
On Subjective Uncertainty Quantification and Calibration in Natural Language Generation
Ziyu Wang, Christopher C. Holmes; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3799-3807
Primal-Dual Spectral Representation for Off-policy Evaluation
Yang Hu, Tianyi Chen, Na Li, Kai Wang, Bo Dai; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3808-3816
Multi-marginal Schrödinger Bridges with Iterative Reference Refinement
Yunyi Shen, Renato Berlinghieri, Tamara Broderick; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3817-3825
RTD-Lite: Scalable Topological Analysis for Comparing Weighted Graphs in Learning Tasks
Eduard Tulchinskii, Daria Voronkova, Ilya Trofimov, Evgeny Burnaev, Serguei Barannikov; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3826-3834
Stochastic Compositional Minimax Optimization with Provable Convergence Guarantees
Yuyang Deng, Fuli Qiao, Mehrdad Mahdavi; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3835-3843
Tighter Confidence Bounds for Sequential Kernel Regression
Hamish Flynn, David Reeb; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3844-3852
Adapting to Online Distribution Shifts in Deep Learning: A Black-Box Approach
Dheeraj Baby, Boran Han, Shuai Zhang, Cuixiong Hu, Bernie Wang, Yu-Xiang Wang; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3853-3861
InnerThoughts: Disentangling Representations and Predictions in Large Language Models
Didier Chételat, Joseph Cotnareanu, Rylee Thompson, Yingxue Zhang, Mark Coates; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3862-3870
Risk-sensitive Bandits: Arm Mixture Optimality and Regret-efficient Algorithms
Meltem Tatlı, Arpan Mukherjee, Prashanth L. A., Karthikeyan Shanmugam, Ali Tajer; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3871-3879
Semiparametric conformal prediction
Ji Won Park, Kyunghyun Cho; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3880-3888
Learning Geometrically-Informed Lyapunov Functions with Deep Diffeomorphic RBF Networks
Samuel Tesfazgi, Leonhard Sprandl, Sandra Hirche; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3889-3897
Max-Rank: Efficient Multiple Testing for Conformal Prediction
Alexander Timans, Christoph-Nikolas Straehle, Kaspar Sakmann, Christian A. Naesseth, Eric Nalisnick; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3898-3906
Near-Optimal Sample Complexity for Iterated CVaR Reinforcement Learning with a Generative Model
Zilong Deng, Simon Khan, Shaofeng Zou; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3907-3915
Steinmetz Neural Networks for Complex-Valued Data
Shyam Venkatasubramanian, Ali Pezeshki, Vahid Tarokh; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3916-3924
Feasible Learning
Juan Ramirez, Ignacio Hounie, Juan Elenter, Jose Gallego-Posada, Meraj Hashemizadeh, Alejandro Ribeiro, Simon Lacoste-Julien; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3925-3933
Task Shift: From Classification to Regression in Overparameterized Linear Models
Tyler LaBonte, Kuo-Wei Lai, Vidya Muthukumar; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3934-3942
Fast Convergence of Softmax Policy Mirror Ascent
Reza Asad, Reza Babanezhad Harikandeh, Issam H. Laradji, Nicolas Le Roux, Sharan Vaswani; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3943-3951
Scalable Implicit Graphon Learning
Ali Azizpour, Nicolas Zilberstein, Santiago Segarra; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3952-3960
Application of Structured State Space Models to High energy physics with locality sensitive hashing
Cheng Jiang, Sitian Qian; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3961-3969
Analysis of Two-Stage Rollout Designs with Clustering for Causal Inference under Network Interference
Mayleen Cortez-Rodriguez, Matthew Eichhorn, Christina Yu; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3970-3978
The Size of Teachers as a Measure of Data Complexity: PAC-Bayes Excess Risk Bounds and Scaling Laws
Gintare Karolina Dziugaite, Daniel M. Roy; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3979-3987
DDEQs: Distributional Deep Equilibrium Models through Wasserstein Gradient Flows
Jonathan Geuter, Clément Bonet, Anna Korba, David Alvarez-Melis; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3988-3996
Bridging the Theoretical Gap in Randomized Smoothing
Blaise Delattre, Paul Caillon, Quentin Barthélemy, Erwan Fagnou, Alexandre Allauzen; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:3997-4005
Distributional Off-policy Evaluation with Bellman Residual Minimization
Sungee Hong, Zhengling Qi, Raymond K. W. Wong; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4006-4014
Theory of Agreement-on-the-Line in Linear Models and Gaussian Data
Christina Baek, Aditi Raghunathan, J Zico Kolter; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4015-4023
SteinDreamer: Variance Reduction for Text-to-3D Score Distillation via Stein Identity
Peihao Wang, Zhiwen Fan, Dejia Xu, Dilin Wang, Sreyas Mohan, Forrest Iandola, Rakesh Ranjan, Yilei Li, Qiang Liu, Zhangyang Wang, Vikas Chandra; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4024-4032
Theoretical Analysis of Leave-one-out Cross Validation for Non-differentiable Penalties under High-dimensional Settings
Haolin Zou, Arnab Auddy, Kamiar Rahnama Rad, Arian Maleki; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4033-4041
Sampling from the Random Linear Model via Stochastic Localization Up to the AMP Threshold
Han Cui, Zhiyuan Yu, Jingbo Liu; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4042-4050
qPOTS: Efficient Batch Multiobjective Bayesian Optimization via Pareto Optimal Thompson Sampling
Ashwin Renganathan, Kade Carlson; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4051-4059
Estimating the Spectral Moments of the Kernel Integral Operator from Finite Sample Matrices
Chanwoo Chun, SueYeon Chung, Daniel Lee; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4060-4068
Enhancing Feature-Specific Data Protection via Bayesian Coordinate Differential Privacy
Maryam Aliakbarpour, Syomantak Chaudhuri, Thomas Courtade, Alireza Fallah, Michael Jordan; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4069-4077
Bayesian Principles Improve Prompt Learning In Vision-Language Models
Mingyu Kim, Jongwoo Ko, Mijung Park; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4078-4086
Unbiased and Sign Compression in Distributed Learning: Comparing Noise Resilience via SDEs
Enea Monzio Compagnoni, Rustem Islamov, Frank Norbert Proske, Aurelien Lucchi; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4087-4095
Privacy in Metalearning and Multitask Learning: Modeling and Separations
Maryam Aliakbarpour, Konstantina Bairaktari, Adam Smith, Marika Swanberg, Jonathan Ullman; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4096-4104
Visualizing token importance for black-box language models
Paulius Rauba, Qiyao Wei, Mihaela van der Schaar; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4105-4113
Tight Analysis of Difference-of-Convex Algorithm (DCA) Improves Convergence Rates for Proximal Gradient Descent
Teodor Rotaru, Panagiotis Patrinos, François Glineur; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4114-4122
All or None: Identifiable Linear Properties of Next-Token Predictors in Language Modeling
Emanuele Marconato, Sebastien Lachapelle, Sebastian Weichwald, Luigi Gresele; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4123-4131
Learning High-dimensional Gaussians from Censored Data
Arnab Bhattacharyya, Constantinos Costis Daskalakis, Themis Gouleakis, Yuhao Wang; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4132-4140
Deep Generative Quantile Bayes
Jungeum Kim, Percy S. Zhai, Veronika Rockova; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4141-4149
Double Debiased Machine Learning for Mediation Analysis with Continuous Treatments
Houssam Zenati, Judith Abécassis, Julie Josse, Bertrand Thirion; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4150-4158
InfoNCE: Identifying the Gap Between Theory and Practice
Evgenia Rusak, Patrik Reizinger, Attila Juhos, Oliver Bringmann, Roland S. Zimmermann, Wieland Brendel; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4159-4167
Achieving $\widetilde\mathcalO(\sqrtT)$ Regret in Average-Reward POMDPs with Known Observation Models
Alessio Russo, Alberto Maria Metelli, Marcello Restelli; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4168-4176
Approximate Equivariance in Reinforcement Learning
Jung Yeon Park, Sujay Bhatt, Sihan Zeng, Lawson L.S. Wong, Alec Koppel, Sumitra Ganesh, Robin Walters; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4177-4185
The cost of local and global fairness in Federated Learning
Yuying Duan, Gelei Xu, Yiyu Shi, Michael Lemmon; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4186-4194
Local Stochastic Sensitivity Analysis For Dynamical Systems
Nishant Panda, Jehanzeb H Chaudhry, Natalie Klein, James Carzon, Troy Butler; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4195-4203
Learning Gaussian Multi-Index Models with Gradient Flow: Time Complexity and Directional Convergence
Berfin Simsek, Amire Bendjeddou, Daniel Hsu; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4204-4212
Variance-Aware Linear UCB with Deep Representation for Neural Contextual Bandits
Ha Manh Bui, Enrique Mallada, Anqi Liu; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4213-4221
Robust Estimation in metric spaces: Achieving Exponential Concentration with a Fréchet Median
Jakwang Kim, Jiyoung Park, Anirban Bhattacharya; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4222-4230
From Deep Additive Kernel Learning to Last-Layer Bayesian Neural Networks via Induced Prior Approximation
Wenyuan Zhao, Haoyuan Chen, Tie Liu, Rui Tuo, Chao Tian; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4231-4239
Effective Bayesian Causal Inference via Structural Marginalisation and Autoregressive Orders
Christian Toth, Christian Knoll, Franz Pernkopf, Robert Peharz; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4240-4248
Linear Submodular Maximization with Bandit Feedback
Wenjing Chen, Victoria G. Crawford; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4249-4257
Cross-modality Matching and Prediction of Perturbation Responses with Labeled Gromov-Wasserstein Optimal Transport
Jayoung Ryu, Charlotte Bunne, Luca Pinello, Aviv Regev, Romain Lopez; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4258-4266
Signal Recovery from Random Dot-Product Graphs under Local Differential Privacy
Siddharth Vishwanath, Jonathan Hehir; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4267-4275
Synthetic Potential Outcomes and Causal Mixture Identifiability
Bijan Mazaheri, Chandler Squires, Caroline Uhler; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4276-4284
Characterizing the Accuracy-Communication-Privacy Trade-off in Distributed Stochastic Convex Optimization
Sudeep Salgia, Nikola Pavlovic, Yuejie Chi, Qing Zhao; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4285-4293
Time-varying Gaussian Process Bandits with Unknown Prior
Juliusz Ziomek, Masaki Adachi, Michael A Osborne; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4294-4302
Logarithmic Neyman Regret for Adaptive Estimation of the Average Treatment Effect
Ojash Neopane, Aaditya Ramdas, Aarti Singh; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4303-4311
Behavior-Inspired Neural Networks for Relational Inference
Yulong Yang, Bowen Feng, Keqin Wang, Naomi Leonard, Adji Bousso Dieng, Christine Allen-Blanchette; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4312-4320
MODL: Multilearner Online Deep Learning
Antonios Valkanas, Boris N. Oreshkin, Mark Coates; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4321-4329
Active Feature Acquisition for Personalised Treatment Assignment
Julianna Piskorz, Nicolás Astorga, Jeroen Berrevoets, Mihaela van der Schaar; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4330-4338
ScoreFusion: Fusing Score-based Generative Models via Kullback–Leibler Barycenters
Hao Liu, Tony Junze Ye, Jose Blanchet, Nian Si; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4339-4347
Loss Gradient Gaussian Width based Generalization and Optimization Guarantees
Arindam Banerjee, Qiaobo Li, Yingxue Zhou; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4348-4356
On the Power of Multitask Representation Learning with Gradient Descent
Qiaobo Li, Zixiang Chen, Yihe Deng, Yiwen Kou, Yuan Cao, Quanquan Gu; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4357-4365
Graph Machine Learning based Doubly Robust Estimator for Network Causal Effects
Seyedeh Baharan Khatami, Harsh Parikh, Haowei Chen, Sudeepa Roy, Babak Salimi; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4366-4374
Cross-Modal Imputation and Uncertainty Estimation for Spatial Transcriptomics
Xiangyu Guo, Ricardo Henao; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4375-4383
M$^2$AD: Multi-Sensor Multi-System Anomaly Detection through Global Scoring and Calibrated Thresholding
Sarah Alnegheimish, Zelin He, Matthew Reimherr, Akash Chandrayan, Abhinav Pradhan, Luca D’Angelo; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4384-4392
Prepacking: A Simple Method for Fast Prefilling and Increased Throughput in Large Language Models
Siyan Zhao, Daniel Mingyi Israel, Guy Van den Broeck, Aditya Grover; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4393-4401
Stochastic Rounding for LLM Training: Theory and Practice
Kaan Ozkara, Tao Yu, Youngsuk Park; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4402-4410
Posterior Mean Matching: Generative Modeling through Online Bayesian Inference
Sebastian Salazar, Michal Kucer, Yixin Wang, Emily Casleton, David Blei; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4411-4419
Offline Multi-task Transfer RL with Representational Penalization
Avinandan Bose, Simon Shaolei Du, Maryam Fazel; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4420-4428
Corruption Robust Offline Reinforcement Learning with Human Feedback
Debmalya Mandal, Andi Nika, Parameswaran Kamalaruban, Adish Singla, Goran Radanovic; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4429-4437
Keeping up with dynamic attackers: Certifying robustness to adaptive online data poisoning
Avinandan Bose, Laurent Lessard, Maryam Fazel, Krishnamurthy Dj Dvijotham; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4438-4446
Bypassing the Exponential Dependency: Looped Transformers Efficiently Learn In-context by Multi-step Gradient Descent
Bo Chen, Xiaoyu Li, Yingyu Liang, Zhenmei Shi, Zhao Song; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4447-4455
Online Assortment and Price Optimization Under Contextual Choice Models
Yigit Efe Erginbas, Thomas Courtade, Kannan Ramchandran; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4456-4464
SINE: Scalable MPE Inference for Probabilistic Graphical Models using Advanced Neural Embeddings
Shivvrat Arya, Tahrima Rahman, Vibhav Giridhar Gogate; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4465-4473
Quantifying Knowledge Distillation using Partial Information Decomposition
Pasan Dissanayake, Faisal Hamman, Barproda Halder, Ilia Sucholutsky, Qiuyi Zhang, Sanghamitra Dutta; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4474-4482
Efficient and Asymptotically Unbiased Constrained Decoding for Large Language Models
Haotian Ye, Himanshu Jain, Chong You, Ananda Theertha Suresh, Haowei Lin, James Zou, Felix Yu; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4483-4491
Cost-Aware Optimal Pairwise Pure Exploration
Di Wu, Chengshuai Shi, Ruida Zhou, Cong Shen; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4492-4500
Understanding Expert Structures on Minimax Parameter Estimation in Contaminated Mixture of Experts
Fanqi Yan, Huy Nguyen, Le Quang Dung, Pedram Akbarian, Nhat Ho; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4501-4509
Batch, match, and patch: low-rank approximations for score-based variational inference
Chirag Modi, Diana Cai, Lawrence K. Saul; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4510-4518
Stochastic Weight Sharing for Bayesian Neural Networks
Moule Lin, Shuhao Guan, Weipeng Jing, Goetz Botterweck, Andrea Patane; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4519-4527
Beyond Discretization: Learning the Optimal Solution Path
Qiran Dong, Paul Grigas, Vishal Gupta; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4528-4536
Faster WIND: Accelerating Iterative Best-of-$N$ Distillation for LLM Alignment
Tong Yang, Jincheng Mei, Hanjun Dai, Zixin Wen, Shicong Cen, Dale Schuurmans, Yuejie Chi, Bo Dai; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4537-4545
Causal Temporal Regime Structure Learning
Abdellah Rahmani, Pascal Frossard; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4546-4554
Linearized Wasserstein Barycenters: Synthesis, Analysis, Representational Capacity, and Applications
Matthew Werenski, Brendan Mallery, Shuchin Aeron, James M. Murphy; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4555-4563
General Staircase Mechanisms for Optimal Differential Privacy
Alex Kulesza, Ananda Theertha Suresh, Yuyan Wang; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4564-4572
Understanding the Effect of GCN Convolutions in Regression Tasks
Juntong Chen, Johannes Schmidt-Hieber, Claire Donnat, Olga Klopp; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4573-4581
Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints
Lingkai Kong, Yuanqi Du, Wenhao Mu, Kirill Neklyudov, Valentin De Bortoli, Dongxia Wu, Haorui Wang, Aaron M Ferber, Yian Ma, Carla P Gomes, Chao Zhang; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4582-4590
Learning Pareto manifolds in high dimensions: How can regularization help?
Tobias Wegel, Filip Kovačević, Alexandru Tifrea, Fanny Yang; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4591-4599
Optimal Stochastic Trace Estimation in Generative Modeling
Xinyang Liu, Hengrong Du, Wei Deng, Ruqi Zhang; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4600-4608
Beyond Size-Based Metrics: Measuring Task-Specific Complexity in Symbolic Regression
Krzysztof Kacprzyk, Mihaela van der Schaar; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4609-4617
Differentially Private Kernelized Contextual Bandits
Nikola Pavlovic, Sudeep Salgia, Qing Zhao; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4618-4626
Federated Communication-Efficient Multi-Objective Optimization
Baris Askin, Pranay Sharma, Gauri Joshi, Carlee Joe-Wong; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4627-4635
Understanding the Learning Dynamics of LoRA: A Gradient Flow Perspective on Low-Rank Adaptation in Matrix Factorization
Ziqing Xu, Hancheng Min, Lachlan Ewen MacDonald, Jinqi Luo, Salma Tarmoun, Enrique Mallada, Rene Vidal; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4636-4644
Variational Schrödinger Momentum Diffusion
Kevin Rojas, Yixin Tan, Molei Tao, Yuriy Nevmyvaka, Wei Deng; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4645-4653
Learning to Forget: Bayesian Time Series Forecasting using Recurrent Sparse Spectrum Signature Gaussian Processes
Csaba Tóth, Masaki Adachi, Michael A Osborne, Harald Oberhauser; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4654-4662
The Uniformly Rotated Mondrian Kernel
Calvin Osborne, Eliza O’Reilly; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4663-4671
Adversarial Vulnerabilities in Large Language Models for Time Series Forecasting
Fuqiang Liu, Sicong Jiang, Luis Miranda-Moreno, Seongjin Choi, Lijun Sun; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4672-4680
Variational Adversarial Training Towards Policies with Improved Robustness
Juncheng Dong, Hao-Lun Hsu, Qitong Gao, Vahid Tarokh, Miroslav Pajic; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4681-4689
Testing Conditional Independence with Deep Neural Network Based Binary Expansion Testing (DeepBET)
Yang Yang, Kai Zhang, Ping-Shou Zhong; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4690-4698
Order-Optimal Regret in Distributed Kernel Bandits using Uniform Sampling with Shared Randomness
Nikola Pavlovic, Sudeep Salgia, Qing Zhao; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4699-4707
On the Consistent Recovery of Joint Distributions from Conditionals
Mahbod Majid, Rattana Pukdee, Vishwajeet Agrawal, Burak Varıcı, Pradeep Kumar Ravikumar; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4708-4716
Transfer Neyman-Pearson Algorithm for Outlier Detection
Mohammadreza Mousavi Kalan, Eitan J. Neugut, Samory Kpotufe; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4717-4725
I-trustworthy Models. A framework for trustworthiness evaluation of probabilistic classifiers
Ritwik Vashistha, Arya Farahi; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4726-4734
Quantile Additive Trend Filtering
Zhi Zhang, Kyle Ritscher, OSCAR HERNAN MADRID PADILLA; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4735-4743
A Computation-Efficient Method of Measuring Dataset Quality based on the Coverage of the Dataset
Beomjun Kim, Jaehwan Kim, Kangyeon Kim, Sunwoo Kim, Heejin Ahn; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4744-4752
Invariant Link Selector for Spatial-Temporal Out-of-Distribution Problem
Katherine Tieu, Dongqi Fu, Jun Wu, Jingrui He; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4753-4761
Advancing Fairness in Precision Medicine: A Universal Framework for Optimal Treatment Estimation in Censored Data
Hongni Wang, Junxi Zhang, Na Li, Linglong Kong, Bei Jiang, Xiaodong Yan; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4762-4770
A Shapley-value Guided Rationale Editor for Rationale Learning
Zixin Kuang, Meng-Fen Chiang, Wang-Chien Lee; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4771-4779
Bilevel Reinforcement Learning via the Development of Hyper-gradient without Lower-Level Convexity
Yan Yang, Bin Gao, Ya-xiang Yuan; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4780-4788
Regularity in Canonicalized Models: A Theoretical Perspective
Behrooz Tahmasebi, Stefanie Jegelka; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4789-4797
Graph-based Complexity for Causal Effect by Empirical Plug-in
Rina Dechter, Anna K Raichev, Jin Tian, Alexander Ihler; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4798-4806
Conditional simulation via entropic optimal transport: Toward non-parametric estimation of conditional Brenier maps
Ricardo Baptista, Aram-Alexandre Pooladian, Michael Brennan, Youssef Marzouk, Jonathan Niles-Weed; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4807-4815
A Robust Kernel Statistical Test of Invariance: Detecting Subtle Asymmetries
Ashkan Soleymani, Behrooz Tahmasebi, Stefanie Jegelka, Patrick Jaillet; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4816-4824
Leveraging Frozen Batch Normalization for Co-Training in Source-Free Domain Adaptation
Xianwen Deng, Yijun Wang, Zhi Xue; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4825-4833
Structure based SAT dataset for analysing GNN generalisation
Yi Fu, Anthony Tompkins, Yang Song, Maurice Pagnucco; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4834-4842
How Well Can Transformers Emulate In-Context Newton’s Method?
Angeliki Giannou, Liu Yang, Tianhao Wang, Dimitris Papailiopoulos, Jason D. Lee; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4843-4851
Nonparametric Distributional Regression via Quantile Regression
Cheng Peng, Stan Uryasev; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4852-4860
Learning Stochastic Nonlinear Dynamics with Embedded Latent Transfer Operators
Naichang Ke, Ryogo Tanaka, Yoshinobu Kawahara; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4861-4869
Deep Clustering via Probabilistic Ratio-Cut Optimization
Ayoub Ghriss, Claire Monteleoni; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4870-4878
Gaussian Mean Testing under Truncation
Clement Louis Canonne, Themis Gouleakis, Yuhao Wang, Qiping Yang; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4879-4887
Conformal Prediction Under Generalized Covariate Shift with Posterior Drift
Baozhen Wang, Xingye Qiao; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4888-4896
Robust Offline Policy Learning with Observational Data from Multiple Sources
Aldo Gael Carranza, Susan Athey; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4897-4905
Mixed-Feature Logistic Regression Robust to Distribution Shifts
Qingshi Sun, Nathan Justin, Andres Gomez, Phebe Vayanos; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4906-4914
Algorithmic Accountability in Small Data: Sample-Size-Induced Bias Within Classification Metrics
Jarren Briscoe, Garrett Kepler, Daryl Robert DeFord, Assefaw Gebremedhin; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4915-4923
Knowledge Graph Completion with Mixed Geometry Tensor Factorization
Viacheslav Yusupov, Maxim Rakhuba, Evgeny Frolov; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4924-4932
Unconditionally Calibrated Priors for Beta Mixture Density Networks
Alix Lhéritier, Maurizio Filippone; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4933-4941
Black-Box Uniform Stability for Non-Euclidean Empirical Risk Minimization
Simon Vary, David Martínez-Rubio, Patrick Rebeschini; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4942-4950
Weighted Euclidean Distance Matrices over Mixed Continuous and Categorical Inputs for Gaussian Process Models
Mingyu Pu, Wang Songhao, Haowei Wang, Szu Hui Ng; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4951-4959
Robust Classification by Coupling Data Mollification with Label Smoothing
Markus Heinonen, Ba-Hien Tran, Michael Kampffmeyer, Maurizio Filippone; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4960-4968
Towards Regulatory-Confirmed Adaptive Clinical Trials: Machine Learning Opportunities and Solutions
Omer Noy Klein, Alihan Hüyük, Ron Shamir, Uri Shalit, Mihaela van der Schaar; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4969-4977
Wasserstein Distributionally Robust Bayesian Optimization with Continuous Context
Francesco Micheli, Efe C. Balta, Anastasios Tsiamis, John Lygeros; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4978-4986
Noise-Aware Differentially Private Variational Inference
Talal Alrawajfeh, Joonas Jälkö, Antti Honkela; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4987-4995
LITE: Efficiently Estimating Gaussian Probability of Maximality
Nicolas Menet, Jonas Hübotter, Parnian Kassraie, Andreas Krause; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:4996-5004
Counting Graphlets of Size k under Local Differential Privacy
Vorapong Suppakitpaisarn, Donlapark Ponnoprat, Nicha Hirankarn, Quentin Hillebrand; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:5005-5013
Sampling from Bayesian Neural Network Posteriors with Symmetric Minibatch Splitting Langevin Dynamics
Daniel Paulin, Peter A. Whalley, Neil K. Chada, Benedict J. Leimkuhler; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:5014-5022
Refined Analysis of Constant Step Size Federated Averaging and Federated Richardson-Romberg Extrapolation
Paul Mangold, Alain Oliviero Durmus, Aymeric Dieuleveut, Sergey Samsonov, Eric Moulines; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:5023-5031
On Local Posterior Structure in Deep Ensembles
Mikkel Jordahn, Jonas Vestergaard Jensen, Mikkel N. Schmidt, Michael Riis Andersen; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:5032-5040
Personalizing Low-Rank Bayesian Neural Networks Via Federated Learning
Boning Zhang, Dongzhu Liu, Osvaldo Simeone, Guanchu Wang, Dimitrios Pezaros, Guangxu Zhu; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:5041-5049
Statistical Guarantees for Lifelong Reinforcement Learning using PAC-Bayes Theory
Zhi Zhang, Chris Chow, Yasi Zhang, Yanchao Sun, Haochen Zhang, Eric Hanchen Jiang, Han Liu, Furong Huang, Yuchen Cui, OSCAR HERNAN MADRID PADILLA; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:5050-5058
Level Set Teleportation: An Optimization Perspective
Aaron Mishkin, Alberto Bietti, Robert M. Gower; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:5059-5067
On the Convergence of Continual Federated Learning Using Incrementally Aggregated Gradients
Satish Kumar Keshri, Nazreen Shah, Ranjitha Prasad; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:5068-5076
Analyzing Generative Models by Manifold Entropic Metrics
Daniel Galperin, Ullrich Koethe; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:5077-5085
DPFL: Decentralized Personalized Federated Learning
Salma Kharrat, Marco Canini, Samuel Horváth; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:5086-5094
Density Ratio-based Proxy Causal Learning Without Density Ratios
Bariscan Bozkurt, Ben Deaner, Dimitri Meunier, Liyuan Xu, Arthur Gretton; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:5095-5103
Certifiably Quantisation-Robust training and inference of Neural Networks
Hue Dang, Matthew Robert Wicker, Goetz Botterweck, Andrea Patane; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:5104-5112
AlleNoise - large-scale text classification benchmark dataset with real-world label noise
Alicja Rączkowska, Aleksandra Osowska-Kurczab, Jacek Szczerbiński, Kalina Jasinska-Kobus, Klaudia Nazarko; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:5113-5121
Strategic Conformal Prediction
Daniel Csillag, Claudio Jose Struchiner, Guilherme Tegoni Goedert; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:5122-5130
Hypernym Bias: Unraveling Deep Classifier Training Dynamics through the Lens of Class Hierarchy
Roman Malashin, Yachnaya Valeria, Alexandr V. Mullin; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:5131-5139
Unifying Feature-Based Explanations with Functional ANOVA and Cooperative Game Theory
Fabian Fumagalli, Maximilian Muschalik, Eyke Hüllermeier, Barbara Hammer, Julia Herbinger; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:5140-5148
M-HOF-Opt: Multi-Objective Hierarchical Output Feedback Optimization via Multiplier Induced Loss Landscape Scheduling
Xudong Sun, Nutan Chen, Alexej Gossmann, Yu Xing, Matteo Wohlrapp, Emilio Dorigatti, Carla Feistner, Felix Drost, Daniele Scarcella, Lisa Helen Beer, Carsten Marr; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:5149-5157
An Empirical Bernstein Inequality for Dependent Data in Hilbert Spaces and Applications
Erfan Mirzaei, Andreas Maurer, Vladimir R Kostic, Massimiliano Pontil; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:5158-5166
Training Neural Samplers with Reverse Diffusive KL Divergence
Jiajun He, Wenlin Chen, Mingtian Zhang, David Barber, José Miguel Hernández-Lobato; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:5167-5175
Every Call is Precious: Global Optimization of Black-Box Functions with Unknown Lipschitz Constants
Fares Fourati, Salma Kharrat, Vaneet Aggarwal, Mohamed-Slim Alouini; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:5176-5184
Mean-Field Microcanonical Gradient Descent
Marcus Häggbom, Morten Karlsmark, Joakim Andén; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:5185-5193
Clustering Context in Off-Policy Evaluation
Daniel Guzman Olivares, Philipp Schmidt, Jacek Golebiowski, Artur Bekasov; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:5194-5202
Task-Driven Discrete Representation Learning
Long Tung Vuong; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:5203-5211
Emergence of Globally Attracting Fixed Points in Deep Neural Networks With Nonlinear Activations
Amir Joudaki, Thomas Hofmann; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:5212-5220
Exposing Privacy Gaps: Membership Inference Attack on Preference Data for LLM Alignment
Qizhang Feng, Siva Rajesh Kasa, SANTHOSH KUMAR KASA, Hyokun Yun, Choon Hui Teo, Sravan Babu Bodapati; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:5221-5229
The Strong Product Model for Network Inference without Independence Assumptions
Bailey Andrew, David Robert Westhead, Luisa Cutillo; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:5230-5238
A Convex Relaxation Approach to Generalization Analysis for Parallel Positively Homogeneous Networks
Uday Kiran Reddy Tadipatri, Benjamin David Haeffele, Joshua Agterberg, Rene Vidal; Proceedings of The 28th International Conference on Artificial Intelligence and Statistics, PMLR 258:5239-5247
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