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Editors: Silvia Chiappa, Roberto Calandra
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Linearly Convergent Frank-Wolfe with Backtracking Line-Search
; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1-10
Guarantees of Stochastic Greedy Algorithms for Non-monotone Submodular Maximization with Cardinality Constraint
Shinsaku Sakaue; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:11-21
On Maximization of Weakly Modular Functions: Guarantees of Multi-stage Algorithms, Tractability, and Hardness
Shinsaku Sakaue; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:22-33
Adaptive Trade-Offs in Off-Policy Learning
Mark Rowland, Will Dabney, Remi Munos; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:34-44
Conditional Importance Sampling for Off-Policy Learning
Mark Rowland, Anna Harutyunyan, Hado Hasselt, Diana Borsa, Tom Schaul, Remi Munos, Will Dabney; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:45-55
Multiplicative Gaussian Particle Filter
Xuan Su, Wee Sun Lee, Zhen Zhang; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:56-65
Stretching the Effectiveness of MLE from Accuracy to Bias for Pairwise Comparisons
Jingyan Wang, Nihar Shah, R Ravi; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:66-76
Fast and Accurate Ranking Regression
Ilkay Yildiz, Jennifer Dy, Deniz Erdogmus, Jayashree Kalpathy-Cramer, Susan Ostmo, J. Peter Campbell, Michael F. Chiang, Stratis Ioannidis; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:77-88
Tight Analysis of Privacy and Utility Tradeoff in Approximate Differential Privacy
Quan Geng, Wei Ding, Ruiqi Guo, Sanjiv Kumar; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:89-99
Long-and Short-Term Forecasting for Portfolio Selection with Transaction Costs
Guy Uziel, Ran El-Yaniv; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:100-110
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Nonparametric Sequential Prediction While Deep Learning the Kernel
Guy Uziel; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:111-121
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Improving Maximum Likelihood Training for Text Generation with Density Ratio Estimation
Yuxuan Song, Ning Miao, Hao Zhou, Lantao Yu, Mingxuan Wang, Lei Li; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:122-132
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A Double Residual Compression Algorithm for Efficient Distributed Learning
Xiaorui Liu, Yao Li, Jiliang Tang, Ming Yan; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:133-143
Asynchronous Gibbs Sampling
Alexander Terenin, Daniel Simpson, David Draper; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:144-154
Learning Fair Representations for Kernel Models
Zilong Tan, Samuel Yeom, Matt Fredrikson, Ameet Talwalkar; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:155-166
A Nonparametric Off-Policy Policy Gradient
Samuele Tosatto, Joao Carvalho, Hany Abdulsamad, Jan Peters; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:167-177
Non-Parametric Calibration for Classification
Jonathan Wenger, Hedvig Kjellström, Rudolph Triebel); Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:178-190
Minimax Testing of Identity to a Reference Ergodic Markov Chain
Geoffrey Wolfer, Aryeh Kontorovich; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:191-201
A Linear-time Independence Criterion Based on a Finite Basis Approximation
Longfei Yan, W. Bastiaan Kleijn, Thushara Abhayapala; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:202-212
Minimax Bounds for Structured Prediction Based on Factor Graphs
Kevin Bello, Asish Ghoshal, Jean Honorio; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:213-222
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On the Convergence of SARAH and Beyond
Bingcong Li, Meng Ma, Georgios B. Giannakis; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:223-233
Uncertainty in Neural Networks: Approximately Bayesian Ensembling
Tim Pearce, Felix Leibfried, Alexandra Brintrup; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:234-244
LIBRE: Learning Interpretable Boolean Rule Ensembles
Graziano Mita, Paolo Papotti, Maurizio Filippone, Pietro Michiardi; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:245-255
Marginal Densities, Factor Graph Duality, and High-Temperature Series Expansions
Mehdi Molkaraie; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:256-265
Neighborhood Growth Determines Geometric Priors for Relational Representation Learning
Melanie Weber; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:266-276
Fair Decisions Despite Imperfect Predictions
Niki Kilbertus, Manuel Gomez Rodriguez, Bernhard Schölkopf, Krikamol Muandet, Isabel Valera; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:277-287
A Characterization of Mean Squared Error for Estimator with Bagging
Martin Mihelich, Charles Dognin, Yan Shu, Michael Blot; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:288-297
Uncertainty Quantification for Sparse Deep Learning
Yuexi Wang, Veronika Rockova; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:298-308
Minimizing Dynamic Regret and Adaptive Regret Simultaneously
Lijun Zhang, Shiyin Lu, Tianbao Yang; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:309-319
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A Stein Goodness-of-fit Test for Directional Distributions
Wenkai Xu, Takeru Matsuda; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:320-330
Unsupervised Neural Universal Denoiser for Finite-Input General-Output Noisy Channel
Taeeon Park, Taesup Moon; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:331-340
Leave-One-Out Cross-Validation for Bayesian Model Comparison in Large Data
Måns Magnusson, Aki Vehtari, Johan Jonasson, Michael Andersen; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:341-351
Robust Importance Weighting for Covariate Shift
Fengpei Li, Henry Lam, Siddharth Prusty; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:352-362
Adaptive Online Kernel Sampling for Vertex Classification
Peng Yang, Ping Li; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:363-373
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A Hybrid Stochastic Policy Gradient Algorithm for Reinforcement Learning
Nhan Pham, Lam Nguyen, Dzung Phan, PHUONG HA NGUYEN, Marten Dijk, Quoc Tran-Dinh; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:374-385
Stopping criterion for active learning based on deterministic generalization bounds
Hideaki Ishibashi, Hideitsu Hino; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:386-397
Ivy: Instrumental Variable Synthesis for Causal Inference
Zhaobin Kuang, Frederic Sala, Nimit Sohoni, Sen Wu, Aldo Córdova-Palomera, Jared Dunnmon, James Priest, Christopher Re; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:398-410
High Dimensional Robust Sparse Regression
Liu Liu, Yanyao Shen, Tianyang Li, Constantine Caramanis; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:411-421
Nested-Wasserstein Self-Imitation Learning for Sequence Generation
Ruiyi Zhang, Changyou Chen, Zhe Gan, Zheng Wen, Wenlin Wang, Lawrence Carin; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:422-433
Greed Meets Sparsity: Understanding and Improving Greedy Coordinate Descent for Sparse Optimization
Huang Fang, Zhenan Fan, Yifan Sun, Michael Friedlander; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:434-444
Recommendation on a Budget: Column Space Recovery from Partially Observed Entries with Random or Active Sampling
Carolyn Kim, Mohsen Bayati; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:445-455
Fast Noise Removal for k-Means Clustering
Sungjin Im, Mahshid Montazer Qaem, Benjamin Moseley, Xiaorui Sun, Rudy Zhou; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:456-466
Sketching Transformed Matrices with Applications to Natural Language Processing
Yingyu Liang, Zhao Song, Mengdi Wang, Lin Yang, Xin Yang; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:467-481
Unconditional Coresets for Regularized Loss Minimization
Alireza Samadian, Kirk Pruhs, Benjamin Moseley, Sungjin Im, Ryan Curtin; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:482-492
ASAP: Architecture Search, Anneal and Prune
Asaf Noy, Niv Nayman, Tal Ridnik, Nadav Zamir, Sivan Doveh, Itamar Friedman, Raja Giryes, Lihi Zelnik; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:493-503
Understanding Generalization in Deep Learning via Tensor Methods
Jingling Li, Yanchao Sun, Jiahao Su, Taiji Suzuki, Furong Huang; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:504-515
Accelerating Gradient Boosting Machines
Haihao Lu, Sai Praneeth Karimireddy, Natalia Ponomareva, Vahab Mirrokni; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:516-526
Online Binary Space Partitioning Forests
Xuhui Fan, Bin Li, Scott SIsson; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:527-537
Sparse Hilbert-Schmidt Independence Criterion Regression
Benjamin Poignard, Makoto Yamada; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:538-548
Sharp Thresholds of the Information Cascade Fragility Under a Mismatched Model
Wasim Huleihel, Ofer Shayevitz; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:549-558
Optimal sampling in unbiased active learning
Henrik Imberg, Johan Jonasson, Marina Axelson-Fisk; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:559-569
The Area of the Convex Hull of Sampled Curves: a Robust Functional Statistical Depth measure
Guillaume Staerman, Pavlo Mozharovskyi, Stéphan Clémen\con; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:570-579
Diameter-based Interactive Structure Discovery
Christopher Tosh, Daniel Hsu; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:580-590
Utility/Privacy Trade-off through the lens of Optimal Transport
Etienne Boursier, Vianney Perchet; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:591-601
A Lyapunov analysis for accelerated gradient methods: from deterministic to stochastic case
Maxime Laborde, Adam Oberman; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:602-612
Interpretable Deep Gaussian Processes with Moments
Chi-Ken Lu, Scott Cheng-Hsin Yang, Xiaoran Hao, Patrick Shafto; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:613-623
Approximate Inference in Discrete Distributions with Monte Carlo Tree Search and Value Functions
Lars Buesing, Nicolas Heess, Theophane Weber; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:624-634
Accelerated Bayesian Optimisation through Weight-Prior Tuning
Alistair Shilton, Sunil Gupta, Santu Rana, Pratibha Vellanki, Cheng Li, Svetha Venkatesh, Laurence Park, Alessandra Sutti, David Rubin, Thomas Dorin, Alireza Vahid, Murray Height, Teo Slezak; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:635-645
Variance Reduction for Evolution Strategies via Structured Control Variates
Yunhao Tang, Krzysztof Choromanski, Alp Kucukelbir; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:646-656
Optimization of Graph Total Variation via Active-Set-based Combinatorial Reconditioning
Zhenzhang Ye, Thomas Möllenhoff, Tao Wu, Daniel Cremers; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:657-668
Ordered SGD: A New Stochastic Optimization Framework for Empirical Risk Minimization
Kenji Kawaguchi, Haihao Lu; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:669-679
A Unified Theory of SGD: Variance Reduction, Sampling, Quantization and Coordinate Descent
Eduard Gorbunov, Filip Hanzely, Peter Richtarik; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:680-690
Entropy Weighted Power k-Means Clustering
Saptarshi Chakraborty, Debolina Paul, Swagatam Das, Jason Xu; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:691-701
Identifying and Correcting Label Bias in Machine Learning
Heinrich Jiang, Ofir Nachum; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:702-712
AsyncQVI: Asynchronous-Parallel Q-Value Iteration for Discounted Markov Decision Processes with Near-Optimal Sample Complexity
Yibo Zeng, Fei Feng, Wotao Yin; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:713-723
Active Community Detection with Maximal Expected Model Change
Dan Kushnir, Benjamin Mirabelli; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:724-734
RCD: Repetitive causal discovery of linear non-Gaussian acyclic models with latent confounders
Takashi Nicholas Maeda, Shohei Shimizu; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:735-745
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A Simple Approach for Non-stationary Linear Bandits
Peng Zhao, Lijun Zhang, Yuan Jiang, Zhi-Hua Zhou; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:746-755
Distributionally Robust Formulation and Model Selection for the Graphical Lasso
Pedro Cisneros-Velarde, Alexander Petersen, Sang-Yun Oh; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:756-765
Efficient Spectrum-Revealing CUR Matrix Decomposition
Cheng Chen, Ming Gu, Zhihua Zhang, Weinan Zhang, Yong Yu; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:766-775
Graph DNA: Deep Neighborhood Aware Graph Encoding for Collaborative Filtering
Liwei Wu, Hsiang-Fu Yu, Nikhil Rao, James Sharpnack, Cho-Jui Hsieh; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:776-787
Characterization of Overlap in Observational Studies
Michael Oberst, Fredrik Johansson, Dennis Wei, Tian Gao, Gabriel Brat, David Sontag, Kush Varshney; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:788-798
Modular Block-diagonal Curvature Approximations for Feedforward Architectures
Felix Dangel, Stefan Harmeling, Philipp Hennig; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:799-808
A Unified Statistically Efficient Estimation Framework for Unnormalized Models
Masatoshi Uehara, Takafumi Kanamori, Takashi Takenouchi, Takeru Matsuda; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:809-819
More Powerful Selective Kernel Tests for Feature Selection
Jen Ning Lim, Makoto Yamada, Wittawat Jitkrittum, Yoshikazu Terada, Shigeyuki Matsui, Hidetoshi Shimodaira; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:820-830
Imputation estimators for unnormalized models with missing data
Masatoshi Uehara, Takeru Matsuda, Jae Kwang Kim; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:831-841
Wasserstein Style Transfer
Youssef Mroueh; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:842-852
Elimination of All Bad Local Minima in Deep Learning
Kenji Kawaguchi, Leslie Kaelbling; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:853-863
Fully Decentralized Joint Learning of Personalized Models and Collaboration Graphs
Valentina Zantedeschi, Aurélien Bellet, Marc Tommasi; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:864-874
Formal Limitations on the Measurement of Mutual Information
David McAllester, Karl Stratos; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:875-884
Scalable Feature Selection for (Multitask) Gradient Boosted Trees
Cuize Han, Nikhil Rao, Daria Sorokina, Karthik Subbian; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:885-894
Model-Agnostic Counterfactual Explanations for Consequential Decisions
Amir-Hossein Karimi, Gilles Barthe, Borja Balle, Isabel Valera; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:895-905
Obfuscation via Information Density Estimation
Hsiang Hsu, Shahab Asoodeh, Flavio Calmon; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:906-917
Linear Dynamics: Clustering without identification
Chloe Hsu, Michaela Hardt, Moritz Hardt; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:918-929
Low-rank regularization and solution uniqueness in over-parameterized matrix sensing
Kelly Geyer, Anastasios Kyrillidis, Amir Kalev; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:930-940
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Robustness for Non-Parametric Classification: A Generic Attack and Defense
Yao-Yuan Yang, Cyrus Rashtchian, Yizhen Wang, Kamalika Chaudhuri; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:941-951
Contextual Online False Discovery Rate Control
Shiyun Chen, Shiva Kasiviswanathan; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:952-961
Sequential no-Substitution k-Median-Clustering
Tom Hess, Sivan Sabato; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:962-972
Robust Learning from Discriminative Feature Feedback
Sanjoy Dasgupta, Sivan Sabato; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:973-982
Hermitian matrices for clustering directed graphs: insights and applications
Mihai Cucuringu, Huan Li, He Sun, Luca Zanetti; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:983-992
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Kernel Conditional Density Operators
Ingmar Schuster, Mattes Mollenhauer, Stefan Klus, Krikamol Muandet; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:993-1004
Learning Overlapping Representations for the Estimation of Individualized Treatment Effects
Yao Zhang, Alexis Bellot, Mihaela Schaar; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1005-1014
Additive Tree-Structured Covariance Function for Conditional Parameter Spaces in Bayesian Optimization
Xingchen Ma, Matthew Blaschko; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1015-1025
Asymptotic Analysis of Sampling Estimators for Randomized Numerical Linear Algebra Algorithms
Ping Ma, Xinlian Zhang, Xin Xing, Jingyi Ma, Michael Mahoney; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1026-1035
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The Fast Loaded Dice Roller: A Near-Optimal Exact Sampler for Discrete Probability Distributions
Feras Saad, Cameron Freer, Martin Rinard, Vikash Mansinghka; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1036-1046
A Fast Anderson-Chebyshev Acceleration for Nonlinear Optimization
Zhize Li, Jian Li; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1047-1057
Black Box Submodular Maximization: Discrete and Continuous Settings
Lin Chen, Mingrui Zhang, Hamed Hassani, Amin Karbasi; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1058-1070
Corruption-Tolerant Gaussian Process Bandit Optimization
Ilija Bogunovic, Andreas Krause, Jonathan Scarlett; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1071-1081
On the Convergence Theory of Gradient-Based Model-Agnostic Meta-Learning Algorithms
Alireza Fallah, Aryan Mokhtari, Asuman Ozdaglar; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1082-1092
Alternating Minimization Converges Super-Linearly for Mixed Linear Regression
Avishek Ghosh, Ramchandran Kannan; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1093-1103
Learning Gaussian Graphical Models via Multiplicative Weights
Anamay Chaturvedi, Jonathan Scarlett; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1104-1114
Mitigating Overfitting in Supervised Classification from Two Unlabeled Datasets: A Consistent Risk Correction Approach
Nan Lu, Tianyi Zhang, Gang Niu, Masashi Sugiyama; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1115-1125
Infinitely deep neural networks as diffusion processes
Stefano Peluchetti, Stefano Favaro; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1126-1136
Stable behaviour of infinitely wide deep neural networks
Stefano Peluchetti, Stefano Favaro, Sandra Fortini; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1137-1146
Neural Topic Model with Attention for Supervised Learning
Xinyi Wang, YI YANG; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1147-1156
Causal Mosaic: Cause-Effect Inference via Nonlinear ICA and Ensemble Method
Pengzhou Wu, Kenji Fukumizu; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1157-1167
Stochastic Bandits with Delay-Dependent Payoffs
Leonardo Cella, Nicoló Cesa-Bianchi; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1168-1177
Risk Bounds for Learning Multiple Components with Permutation-Invariant Losses
Fabien Lauer; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1178-1187
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Balancing Learning Speed and Stability in Policy Gradient via Adaptive Exploration
Matteo Papini, Andrea Battistello, Marcello Restelli; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1188-1199
Independent Subspace Analysis for Unsupervised Learning of Disentangled Representations
Jan Stuehmer, Richard Turner, Sebastian Nowozin; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1200-1210
A Practical Algorithm for Multiplayer Bandits when Arm Means Vary Among Players
Abbas Mehrabian, Etienne Boursier, Emilie Kaufmann, Vianney Perchet; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1211-1221
Regularity as Regularization: Smooth and Strongly Convex Brenier Potentials in Optimal Transport
François-Pierre Paty, Alexandre d’Aspremont, Marco Cuturi; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1222-1232
On Generalization Bounds of a Family of Recurrent Neural Networks
Minshuo Chen, Xingguo Li, Tuo Zhao; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1233-1243
Simulator Calibration under Covariate Shift with Kernels
Keiichi Kisamori, Motonobu Kanagawa, Keisuke Yamazaki; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1244-1253
Convergence Rates of Gradient Descent and MM Algorithms for Bradley-Terry Models
Milan Vojnovic, Se-Young Yun, Kaifang Zhou; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1254-1264
A Locally Adaptive Bayesian Cubature Method
Matthew Fisher, Chris Oates, Catherine Powell, Aretha Teckentrup; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1265-1275
Fast and Bayes-consistent nearest neighbors
Klim Efremenko, Aryeh Kontorovich, Moshe Noivirt; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1276-1286
Explaining the Explainer: A First Theoretical Analysis of LIME
Damien Garreau, Ulrike Luxburg; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1287-1296
A Continuous-time Perspective for Modeling Acceleration in Riemannian Optimization
Foivos Alimisis, Antonio Orvieto, Gary Becigneul, Aurelien Lucchi; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1297-1307
Deep Active Learning: Unified and Principled Method for Query and Training
Changjian Shui, Fan Zhou, Christian Gagné, Boyu Wang; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1308-1318
Sparse and Low-rank Tensor Estimation via Cubic Sketchings
Botao Hao, Anru R. Zhang, Guang Cheng; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1319-1330
A nonasymptotic law of iterated logarithm for general M-estimators
Nicolas Schreuder, Victor-Emmanuel Brunel, Arnak Dalalyan; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1331-1341
Robust Stackelberg buyers in repeated auctions
Thomas Nedelec, Clement Calauzenes, Vianney Perchet, Noureddine El Karoui; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1342-1351
Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning
Sebastian Farquhar, Michael A. Osborne, Yarin Gal; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1352-1362
Practical Nonisotropic Monte Carlo Sampling in High Dimensions via Determinantal Point Processes
Krzysztof Choromanski, Aldo Pacchiano, Jack Parker-Holder, Yunhao Tang; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1363-1374
Fast and Furious Convergence: Stochastic Second Order Methods under Interpolation
Si Yi Meng, Sharan Vaswani, Issam Hadj Laradji), Mark Schmidt, Simon Lacoste-Julien; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1375-1386
Two-sample Testing Using Deep Learning
Matthias Kirchler, Shahryar Khorasani, Marius Kloft, Christoph Lippert; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1387-1398
RATQ: A Universal Fixed-Length Quantizer for Stochastic Optimization
Prathamesh Mayekar, Himanshu Tyagi; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1399-1409
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Rep the Set: Neural Networks for Learning Set Representations
Konstantinos Skianis, Giannis Nikolentzos, Stratis Limnios, Michalis Vazirgiannis; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1410-1420
A Multiclass Classification Approach to Label Ranking
Robin Vogel, Stéphan Clémen\con; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1421-1430
Conservative Exploration in Reinforcement Learning
Evrard Garcelon, Mohammad Ghavamzadeh, Alessandro Lazaric, Matteo Pirotta; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1431-1441
A principled approach for generating adversarial images under non-smooth dissimilarity metrics
Aram-Alexandre Pooladian, Chris Finlay, Tim Hoheisel, Adam Oberman; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1442-1452
Regularization via Structural Label Smoothing
Weizhi Li, Gautam Dasarathy, Visar Berisha; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1453-1463
Communication-Efficient Asynchronous Stochastic Frank-Wolfe over Nuclear-norm Balls
Jiacheng Zhuo, Qi Lei, Alex Dimakis, Constantine Caramanis; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1464-1474
Linear Convergence of Adaptive Stochastic Gradient Descent
Yuege Xie, Xiaoxia Wu, Rachel Ward; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1475-1485
Contextual Combinatorial Volatile Multi-armed Bandit with Adaptive Discretization
Andi Nika, Sepehr Elahi, Cem Tekin; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1486-1496
A Unified Analysis of Extra-gradient and Optimistic Gradient Methods for Saddle Point Problems: Proximal Point Approach
Aryan Mokhtari, Asuman Ozdaglar, Sarath Pattathil; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1497-1507
Bandit Convex Optimization in Non-stationary Environments
Peng Zhao, Guanghui Wang, Lijun Zhang, Zhi-Hua Zhou; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1508-1518
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Decentralized Multi-player Multi-armed Bandits with No Collision Information
Chengshuai Shi, Wei Xiong, Cong Shen, Jing Yang; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1519-1528
Bayesian Image Classification with Deep Convolutional Gaussian Processes
Vincent Dutordoir, Mark Wilk, Artem Artemev, James Hensman; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1529-1539
Optimizing Millions of Hyperparameters by Implicit Differentiation
Jonathan Lorraine, Paul Vicol, David Duvenaud; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1540-1552
A Topology Layer for Machine Learning
Rickard Brüel Gabrielsson, Bradley J. Nelson, Anjan Dwaraknath, Primoz Skraba; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1553-1563
Differentiable Feature Selection by Discrete Relaxation
Rishit Sheth, Nicoló Fusi; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1564-1572
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Private Protocols for U-Statistics in the Local Model and Beyond
James Bell, Aurélien Bellet, Adria Gascon, Tejas Kulkarni; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1573-1583
Automatic Differentiation of Some First-Order Methods in Parametric Optimization
Sheheryar Mehmood, Peter Ochs; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1584-1594
DYNOTEARS: Structure Learning from Time-Series Data
Roxana Pamfil, Nisara Sriwattanaworachai, Shaan Desai, Philip Pilgerstorfer, Konstantinos Georgatzis, Paul Beaumont, Bryon Aragam; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1595-1605
Unsupervised Hierarchy Matching with Optimal Transport over Hyperbolic Spaces
David Alvarez-Melis, Youssef Mroueh, Tommi Jaakkola; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1606-1617
Competing Bandits in Matching Markets
Lydia T. Liu, Horia Mania, Michael Jordan; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1618-1628
Revisiting the Landscape of Matrix Factorization
Hossein Valavi, Sulin Liu, Peter Ramadge; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1629-1638
Value Preserving State-Action Abstractions
David Abel, Nate Umbanhowar, Khimya Khetarpal, Dilip Arumugam, Doina Precup, Michael Littman; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1639-1650
GP-VAE: Deep Probabilistic Time Series Imputation
Vincent Fortuin, Dmitry Baranchuk, Gunnar Raetsch, Stephan Mandt; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1651-1661
Communication-Efficient Distributed Optimization in Networks with Gradient Tracking and Variance Reduction
Boyue Li, Shicong Cen, Yuxin Chen, Yuejie Chi; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1662-1672
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Optimized Score Transformation for Fair Classification
Dennis Wei, Karthikeyan Natesan Ramamurthy, Flavio Calmon; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1673-1683
Variational Autoencoders for Sparse and Overdispersed Discrete Data
He Zhao, Piyush Rai, Lan Du, Wray Buntine, Dinh Phung, Mingyuan Zhou; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1684-1694
Spatio-temporal alignments: Optimal transport through space and time
Hicham Janati, Marco Cuturi, Alexandre Gramfort; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1695-1704
Accelerating Smooth Games by Manipulating Spectral Shapes
Waïss Azizian, Damien Scieur, Ioannis Mitliagkas, Simon Lacoste-Julien, Gauthier Gidel; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1705-1715
Langevin Monte Carlo without smoothness
Niladri Chatterji, Jelena Diakonikolas, Michael I. Jordan, Peter Bartlett; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1716-1726
EM Converges for a Mixture of Many Linear Regressions
Jeongyeol Kwon, Constantine Caramanis; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1727-1736
Locally Accelerated Conditional Gradients
Jelena Diakonikolas, Alejandro Carderera, Sebastian Pokutta; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1737-1747
Coping With Simulators That Don’t Always Return
Andrew Warrington, Saeid Naderiparizi, Frank Wood; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1748-1758
Post-Estimation Smoothing: A Simple Baseline for Learning with Side Information
Esther Rolf, Michael I. Jordan, Benjamin Recht; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1759-1769
Equalized odds postprocessing under imperfect group information
Pranjal Awasthi, Matthäus Kleindessner, Jamie Morgenstern; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1770-1780
The True Sample Complexity of Identifying Good Arms
Julian Katz-Samuels, Kevin Jamieson; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1781-1791
Validated Variational Inference via Practical Posterior Error Bounds
Jonathan Huggins, Mikolaj Kasprzak, Trevor Campbell, Tamara Broderick; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1792-1802
A Rule for Gradient Estimator Selection, with an Application to Variational Inference
Tomas Geffner, Justin Domke; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1803-1812
Naive Feature Selection: Sparsity in Naive Bayes
Armin Askari, Alexandre d’Aspremont, Laurent El Ghaoui; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1813-1822
Fixed-confidence guarantees for Bayesian best-arm identification
Xuedong Shang, Rianne Heide, Pierre Menard, Emilie Kaufmann, Michal Valko; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1823-1832
Learning Hierarchical Interactions at Scale: A Convex Optimization Approach
Hussein Hazimeh, Rahul Mazumder; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1833-1843
OSOM: A simultaneously optimal algorithm for multi-armed and linear contextual bandits
Niladri Chatterji, Vidya Muthukumar, Peter Bartlett; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1844-1854
Optimization Methods for Interpretable Differentiable Decision Trees Applied to Reinforcement Learning
Andrew Silva, Taylor Killian, Ivan Jimenez, Sung-Hyun Son, Matthew Gombolay; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1855-1865
Sharp Analysis of Expectation-Maximization for Weakly Identifiable Models
Raaz Dwivedi, Nhat Ho, Koulik Khamaru, Martin Wainwright, Michael Jordan, Bin Yu; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1866-1876
Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theory
Jianyi Zhang, Ruiyi Zhang, Lawrence Carin, Changyou Chen; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1877-1887
Dynamical Systems Theory for Causal Inference with Application to Synthetic Control Methods
Yi Ding, Panos Toulis; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1888-1898
RelatIF: Identifying Explanatory Training Samples via Relative Influence
Elnaz Barshan, Marc-Etienne Brunet, Gintare Karolina Dziugaite; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1899-1909
Ensemble Gaussian Processes with Spectral Features for Online Interactive Learning with Scalability
Qin Lu, Georgios Karanikolas, Yanning Shen, Georgios B. Giannakis; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1910-1920
Distributionally Robust Bayesian Quadrature Optimization
Thanh Nguyen, Sunil Gupta, Huong Ha, Santu Rana, Svetha Venkatesh; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1921-1931
Sparse Orthogonal Variational Inference for Gaussian Processes
Jiaxin Shi, Michalis Titsias, Andriy Mnih; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1932-1942
The Sylvester Graphical Lasso (SyGlasso)
Yu Wang, Byoungwook Jang, Alfred Hero; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1943-1953
Frequentist Regret Bounds for Randomized Least-Squares Value Iteration
Andrea Zanette, David Brandfonbrener, Emma Brunskill, Matteo Pirotta, Alessandro Lazaric; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1954-1964
DAve-QN: A Distributed Averaged Quasi-Newton Method with Local Superlinear Convergence Rate
Saeed Soori, Konstantin Mishchenko, Aryan Mokhtari, Maryam Mehri Dehnavi, Mert Gurbuzbalaban; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1965-1976
Discrete Action On-Policy Learning with Action-Value Critic
Yuguang Yue, Yunhao Tang, Mingzhang Yin, Mingyuan Zhou; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1977-1987
Old Dog Learns New Tricks: Randomized UCB for Bandit Problems
Sharan Vaswani, Abbas Mehrabian, Audrey Durand, Branislav Kveton; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1988-1998
Thompson Sampling for Linearly Constrained Bandits
Vidit Saxena, Joakim Jalden, Joseph Gonzalez; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:1999-2009
Sample Complexity of Reinforcement Learning using Linearly Combined Model Ensembles
Aditya Modi, Nan Jiang, Ambuj Tewari, Satinder Singh; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2010-2020
FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization
Amirhossein Reisizadeh, Aryan Mokhtari, Hamed Hassani, Ali Jadbabaie, Ramtin Pedarsani; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2021-2031
Online Learning Using Only Peer Prediction
Yang Liu, Dave Helmbold; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2032-2042
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Deontological Ethics By Monotonicity Shape Constraints
Serena Wang, Maya Gupta; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2043-2054
On Random Subsampling of Gaussian Process Regression: A Graphon-Based Analysis
Kohei Hayashi, Masaaki Imaizumi, Yuichi Yoshida; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2055-2065
Randomized Exploration in Generalized Linear Bandits
Branislav Kveton, Manzil Zaheer, Csaba Szepesvari, Lihong Li, Mohammad Ghavamzadeh, Craig Boutilier; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2066-2076
Assessing Local Generalization Capability in Deep Models
Huan Wang, Nitish Shirish Keskar, Caiming Xiong, Richard Socher; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2077-2087
Fast Algorithms for Computational Optimal Transport and Wasserstein Barycenter
Wenshuo Guo, Nhat Ho, Michael Jordan; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2088-2097
Adaptive Discretization for Evaluation of Probabilistic Cost Functions
Christoph Zimmer, Danny Driess, Mona Meister, Nguyen-Tuong Duy; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2098-2108
Censored Quantile Regression Forest
Alexander Hanbo Li, Jelena Bradic; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2109-2119
Choosing the Sample with Lowest Loss makes SGD Robust
Vatsal Shah, Xiaoxia Wu, Sujay Sanghavi; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2120-2130
Learning with minibatch Wasserstein : asymptotic and gradient properties
Kilian Fatras, Younes Zine, Rémi Flamary, Remi Gribonval, Nicolas Courty; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2131-2141
AMAGOLD: Amortized Metropolis Adjustment for Efficient Stochastic Gradient MCMC
Ruqi Zhang, A. Feder Cooper, Christopher De Sa; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2142-2152
On casting importance weighted autoencoder to an EM algorithm to learn deep generative models
Dongha Kim, Jaesung Hwang, Yongdai Kim; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2153-2163
Conditional Linear Regression
Diego Calderon, Brendan Juba, Sirui Li, Zongyi Li, Lisa Ruan; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2164-2173
Distributionally Robust Bayesian Optimization
Johannes Kirschner, Ilija Bogunovic, Stefanie Jegelka, Andreas Krause; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2174-2184
On the optimality of kernels for high-dimensional clustering
Leena C Vankadara, Debarghya Ghoshdastidar; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2185-2195
Improved Regret Bounds for Projection-free Bandit Convex Optimization
Dan Garber, Ben Kretzu; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2196-2206
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Variational Autoencoders and Nonlinear ICA: A Unifying Framework
Ilyes Khemakhem, Diederik Kingma, Ricardo Monti, Aapo Hyvarinen; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2207-2217
Online Learning with Continuous Variations: Dynamic Regret and Reductions
Ching-An Cheng, Jonathan Lee, Ken Goldberg, Byron Boots; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2218-2228
An Optimal Algorithm for Bandit Convex Optimization with Strongly-Convex and Smooth Loss
Shinji Ito; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2229-2239
A Deep Generative Model for Fragment-Based Molecule Generation
Marco Podda, Davide Bacciu, Alessio Micheli; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2240-2250
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Deep Structured Mixtures of Gaussian Processes
Martin Trapp, Robert Peharz, Franz Pernkopf, Carl Edward Rasmussen; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2251-2261
Noisy-Input Entropy Search for Efficient Robust Bayesian Optimization
Lukas Fröhlich, Edgar Klenske, Julia Vinogradska, Christian Daniel, Melanie Zeilinger; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2262-2272
Dependent randomized rounding for clustering and partition systems with knapsack constraints
David Harris, Thomas Pensyl, Aravind Srinivasan, Khoa Trinh; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2273-2283
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Domain-Liftability of Relational Marginal Polytopes
Ondrej Kuzelka, Yuyi Wang; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2284-2292
Derivative-Free & Order-Robust Optimisation
Haitham Ammar, Victor Gabillon, Rasul Tutunov, Michal Valko; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2293-2303
Stepwise Model Selection for Sequence Prediction via Deep Kernel Learning
Yao Zhang, Daniel Jarrett, Mihaela Schaar; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2304-2314
Dynamic content based ranking
Seppo Virtanen, Mark Girolami; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2315-2324
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Fairness Evaluation in Presence of Biased Noisy Labels
Riccardo Fogliato, Alexandra Chouldechova, Max G’Sell; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2325-2336
Calibrated Surrogate Maximization of Linear-fractional Utility in Binary Classification
Han Bao, Masashi Sugiyama; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2337-2347
Decentralized gradient methods: does topology matter?
Giovanni Neglia, Chuan Xu, Don Towsley, Gianmarco Calbi; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2348-2358
Truly Batch Model-Free Inverse Reinforcement Learning about Multiple Intentions
Giorgia Ramponi, Amarildo Likmeta, Alberto Maria Metelli, Andrea Tirinzoni, Marcello Restelli; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2359-2369
Beyond exploding and vanishing gradients: analysing RNN training using attractors and smoothness
António H. Ribeiro, Koen Tiels, Luis A. Aguirre, Thomas Schön; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2370-2380
Accelerated Primal-Dual Algorithms for Distributed Smooth Convex Optimization over Networks
Jinming Xu, Ye Tian, Ying Sun, Gesualdo Scutari; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2381-2391
Stochastic Linear Contextual Bandits with Diverse Contexts
Weiqiang Wu, Jing Yang, Cong Shen; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2392-2401
Purifying Interaction Effects with the Functional ANOVA: An Efficient Algorithm for Recovering Identifiable Additive Models
Benjamin Lengerich, Sarah Tan, Chun-Hao Chang, Giles Hooker, Rich Caruana; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2402-2412
Balanced Off-Policy Evaluation in General Action Spaces
Arjun Sondhi, David Arbour, Drew Dimmery; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2413-2423
Approximate Cross-Validation in High Dimensions with Guarantees
William Stephenson, Tamara Broderick; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2424-2434
How fine can fine-tuning be? Learning efficient language models
Evani Radiya-Dixit, Xin Wang; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2435-2443
Interpretable Companions for Black-Box Models
Danqing Pan, Tong Wang, Satoshi Hara; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2444-2454
A PTAS for the Bayesian Thresholding Bandit Problem
Jian Peng, Yue Qin, Yadi Wei, Yuan Zhou; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2455-2464
Learning Rate Adaptation for Differentially Private Learning
Antti Koskela, Antti Honkela; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2465-2475
Thresholding Graph Bandits with GrAPL
Daniel LeJeune, Gautam Dasarathy, Richard Baraniuk; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2476-2485
Bandit optimisation of functions in the Matérn kernel RKHS
David Janz, David Burt, Javier Gonzalez; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2486-2495
Hypothesis Testing Interpretations and Renyi Differential Privacy
Borja Balle, Gilles Barthe, Marco Gaboardi, Justin Hsu, Tetsuya Sato; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2496-2506
Lipschitz Continuous Autoencoders in Application to Anomaly Detection
Young-geun Kim, Yongchan Kwon, Hyunwoong Chang, Myunghee Cho Paik; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2507-2517
Private k-Means Clustering with Stability Assumptions
Moshe Shechner, Or Sheffet, Uri Stemmer; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2518-2528
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Momentum in Reinforcement Learning
Nino Vieillard, Bruno Scherrer, Olivier Pietquin, Matthieu Geist; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2529-2538
A Primal-Dual Solver for Large-Scale Tracking-by-Assignment
Stefan Haller, Mangal Prakash, Lisa Hutschenreiter, Tobias Pietzsch, Carsten Rother, Florian Jug, Paul Swoboda, Bogdan Savchynskyy; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2539-2549
Precision-Recall Curves Using Information Divergence Frontiers
Josip Djolonga, Mario Lucic, Marco Cuturi, Olivier Bachem, Olivier Bousquet, Sylvain Gelly; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2550-2559
Computing Tight Differential Privacy Guarantees Using FFT
Antti Koskela, Joonas Jälkö, Antti Honkela; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2560-2569
Hyperbolic Manifold Regression
Gian Marconi, Carlo Ciliberto, Lorenzo Rosasco; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2570-2580
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Approximate Inference with Wasserstein Gradient Flows
Charlie Frogner, Tomaso Poggio; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2581-2590
Thresholding Bandit Problem with Both Duels and Pulls
Yichong Xu, Xi Chen, Aarti Singh, Artur Dubrawski; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2591-2600
GAIT: A Geometric Approach to Information Theory
Jose Gallego Posada, Ankit Vani, Max Schwarzer, Simon Lacoste-Julien; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2601-2611
On Thompson Sampling for Smoother-than-Lipschitz Bandits
James Grant, David Leslie; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2612-2622
Safe-Bayesian Generalized Linear Regression
Rianne Heide, Alisa Kirichenko, Peter Grunwald, Nishant Mehta; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2623-2633
Efficient Distributed Hessian Free Algorithm for Large-scale Empirical Risk Minimization via Accumulating Sample Strategy
Majid Jahani, Xi He, Chenxin Ma, Aryan Mokhtari, Dheevatsa Mudigere, Alejandro Ribeiro, Martin Takac; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2634-2644
Contextual Constrained Learning for Dose-Finding Clinical Trials
Hyun-Suk Lee, Cong Shen, James Jordon, Mihaela Schaar; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2645-2654
Support recovery and sup-norm convergence rates for sparse pivotal estimation
Mathurin Massias, Quentin Bertrand, Alexandre Gramfort, Joseph Salmon; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2655-2665
Learning Entangled Single-Sample Distributions via Iterative Trimming
Hui Yuan, Yingyu Liang; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2666-2676
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The Quantile Snapshot Scan: Comparing Quantiles of Spatial Data from Two Snapshots in Time
Travis Moore, Wong Weng-Keen; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2677-2686
Statistical guarantees for local graph clustering
Wooseok Ha, Kimon Fountoulakis, Michael Mahoney; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2687-2697
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Learning High-dimensional Gaussian Graphical Models under Total Positivity without Adjustment of Tuning Parameters
Yuhao Wang, Uma Roy, Caroline Uhler; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2698-2708
On Pruning for Score-Based Bayesian Network Structure Learning
Alvaro Henrique Chaim Correia, James Cussens, Cassio de Campos; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2709-2718
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Statistical and Computational Rates in Graph Logistic Regression
Quentin Berthet, Nicolai Baldin; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2719-2730
Kernels over Sets of Finite Sets using RKHS Embeddings, with Application to Bayesian (Combinatorial) Optimization
Poompol Buathong, David Ginsbourger, Tipaluck Krityakierne; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2731-2741
Rk-means: Fast Clustering for Relational Data
Ryan Curtin, Benjamin Moseley, Hung Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2742-2752
Statistical Estimation of the Poincaré constant and Application to Sampling Multimodal Distributions
Loucas Pillaud-Vivien, Francis Bach, Tony Lelièvre, Alessandro Rudi, Gabriel Stoltz; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2753-2763
Integrals over Gaussians under Linear Domain Constraints
Alexandra Gessner, Oindrila Kanjilal, Philipp Hennig; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2764-2774
Taxonomy of Dual Block-Coordinate Ascent Methods for Discrete Energy Minimization
Siddharth Tourani, Alexander Shekhovtsov, Carsten Rother, Bogdan Savchynskyy; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2775-2785
PersLay: A Neural Network Layer for Persistence Diagrams and New Graph Topological Signatures
Mathieu Carriere, Frederic Chazal, Yuichi Ike, Theo Lacombe, Martin Royer, Yuhei Umeda; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2786-2796
MAP Inference for Customized Determinantal Point Processes via Maximum Inner Product Search
Insu Han, Jennifer Gillenwater; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2797-2807
Why Non-myopic Bayesian Optimization is Promising and How Far Should We Look-ahead? A Study via Rollout
Xubo Yue, Raed AL Kontar; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2808-2818
Robust Optimisation Monte Carlo
Borislav Ikonomov, Michael U. Gutmann; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2819-2829
Guaranteed Validity for Empirical Approaches to Adaptive Data Analysis
Ryan Rogers, Aaron Roth, Adam Smith, Nathan Srebro, Om Thakkar, Blake Woodworth; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2830-2840
Fast Markov chain Monte Carlo algorithms via Lie groups
Steve Huntsman; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2841-2851
Efficient Planning under Partial Observability with Unnormalized Q Functions and Spectral Learning
Tianyu Li, Bogdan Mazoure, Doina Precup, Guillaume Rabusseau; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2852-2862
A Tight and Unified Analysis of Gradient-Based Methods for a Whole Spectrum of Differentiable Games
Waïss Azizian, Ioannis Mitliagkas, Simon Lacoste-Julien, Gauthier Gidel; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2863-2873
Doubly Sparse Variational Gaussian Processes
Vincent Adam, Stefanos Eleftheriadis, Artem Artemev, Nicolas Durrande, James Hensman; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2874-2884
Online Convex Optimization with Perturbed Constraints: Optimal Rates against Stronger Benchmarks
Victor Valls, George Iosifidis, Douglas Leith, Leandros Tassiulas; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2885-2895
Persistence Enhanced Graph Neural Network
Qi Zhao, Ze Ye, Chao Chen, Yusu Wang; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2896-2906
Feature relevance quantification in explainable AI: A causal problem
Dominik Janzing, Lenon Minorics, Patrick Bloebaum; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2907-2916
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Neural Decomposition: Functional ANOVA with Variational Autoencoders
Kaspar Märtens, Christopher Yau; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2917-2927
BasisVAE: Translation-invariant feature-level clustering with Variational Autoencoders
Kaspar Märtens, Christopher Yau; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2928-2937
How To Backdoor Federated Learning
Eugene Bagdasaryan, Andreas Veit, Yiqing Hua, Deborah Estrin, Vitaly Shmatikov; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2938-2948
Exploiting Categorical Structure Using Tree-Based Methods
Brian Lucena; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2949-2958
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A Unified Stochastic Gradient Approach to Designing Bayesian-Optimal Experiments
Adam Foster, Martin Jankowiak, Matthew O’Meara, Yee Whye Teh, Tom Rainforth; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2959-2969
Mixed Strategies for Robust Optimization of Unknown Objectives
Pier Giuseppe Sessa, Ilija Bogunovic, Maryam Kamgarpour, Andreas Krause; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2970-2980
Functional Gradient Boosting for Learning Residual-like Networks with Statistical Guarantees
Atsushi Nitanda, Taiji Suzuki; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2981-2991
Solving Discounted Stochastic Two-Player Games with Near-Optimal Time and Sample Complexity
Aaron Sidford, Mengdi Wang, Lin Yang, Yinyu Ye; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2992-3002
Convergence Rates of Smooth Message Passing with Rounding in Entropy-Regularized MAP Inference
Jonathan Lee, Aldo Pacchiano, Michael Jordan; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3003-3014
Finite-Time Error Bounds for Biased Stochastic Approximation with Applications to Q-Learning
Gang Wang, Georgios B. Giannakis; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3015-3024
Automated Augmented Conjugate Inference for Non-conjugate Gaussian Process Models
Theo Galy-Fajou, Florian Wenzel, Manfred Opper; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3025-3035
Bayesian Reinforcement Learning via Deep, Sparse Sampling
Divya Grover, Debabrota Basu, Christos Dimitrakakis; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3036-3045
Deterministic Decoding for Discrete Data in Variational Autoencoders
Daniil Polykovskiy, Dmitry Vetrov; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3046-3056
Monotonic Gaussian Process Flows
Ivan Ustyuzhaninov, Ieva Kazlauskaite, Carl Henrik Ek, Neill Campbell; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3057-3067
Flexible distribution-free conditional predictive bands using density estimators
Rafael Izbicki, Gilson Shimizu, Rafael Stern; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3068-3077
Variational Integrator Networks for Physically Structured Embeddings
Steindor Saemundsson, Alexander Terenin, Katja Hofmann, Marc Deisenroth; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3078-3087
Black-Box Inference for Non-Linear Latent Force Models
Wil Ward, Tom Ryder, Dennis Prangle, Mauricio Alvarez; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3088-3098
Importance Sampling via Local Sensitivity
Anant Raj, Cameron Musco, Lester Mackey; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3099-3109
Convergence Analysis of Block Coordinate Algorithms with Determinantal Sampling
Mojmir Mutny, Michal Derezinski, Andreas Krause; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3110-3120
Bisect and Conquer: Hierarchical Clustering via Max-Uncut Bisection
Vaggos Chatziafratis, Grigory Yaroslavtsev, Euiwoong Lee, Konstantin Makarychev, Sara Ahmadian, Alessandro Epasto, Mohammad Mahdian; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3121-3132
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Laplacian-Regularized Graph Bandits: Algorithms and Theoretical Analysis
Kaige Yang, Laura Toni, Xiaowen Dong; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3133-3143
Enriched mixtures of generalised Gaussian process experts
Charles Gadd, Sara Wade, Alexis Boukouvalas; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3144-3154
Causal Bayesian Optimization
Virginia Aglietti, Xiaoyu Lu, Andrei Paleyes, Javier González; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3155-3164
Linear predictor on linearly-generated data with missing values: non consistency and solutions
Marine Le Morvan, Nicolas Prost, Julie Josse, Erwan Scornet, Gael Varoquaux; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3165-3174
A Novel Confidence-Based Algorithm for Structured Bandits
Andrea Tirinzoni, Alessandro Lazaric, Marcello Restelli; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3175-3185
Quantitative stability of optimal transport maps and linearization of the 2-Wasserstein space
Quentin Mérigot, Alex Delalande, Frederic Chazal; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3186-3196
Bayesian experimental design using regularized determinantal point processes
Michal Derezinski, Feynman Liang, Michael Mahoney; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3197-3207
Non-exchangeable feature allocation models with sublinear growth of the feature sizes
Giuseppe Di Benedetto, Francois Caron, Yee Whye Teh; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3208-3218
Calibrated Prediction with Covariate Shift via Unsupervised Domain Adaptation
Sangdon Park, Osbert Bastani, James Weimer, Insup Lee; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3219-3229
Inference of Dynamic Graph Changes for Functional Connectome
Dingjue Ji, Junwei Lu, Yiliang Zhang, Siyuan Gao, Hongyu Zhao; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3230-3240
An approximate KLD based experimental design for models with intractable likelihoods
Ziqiao Ao, Jinglai Li; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3241-3251
Almost-Matching-Exactly for Treatment Effect Estimation under Network Interference
Usaid Awan, Marco Morucci, Vittorio Orlandi, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3252-3262
“Bring Your Own Greedy”+Max: Near-Optimal 1/2-Approximations for Submodular Knapsack
Grigory Yaroslavtsev, Samson Zhou, Dmitrii Avdiukhin; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3263-3274
Sample complexity bounds for localized sketching
Rakshith Sharma Srinivasa, Mark Davenport, Justin Romberg; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3275-3284
An Optimal Algorithm for Adversarial Bandits with Arbitrary Delays
Julian Zimmert, Yevgeny Seldin; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3285-3294
Learning Dynamic and Personalized Comorbidity Networks from Event Data using Deep Diffusion Processes
Zhaozhi Qian, Ahmed Alaa, Alexis Bellot, Mihaela Schaar, Jem Rashbass; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3295-3305
Tensorized Random Projections
Beheshteh Rakhshan, Guillaume Rabusseau; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3306-3316
Nonparametric Estimation in the Dynamic Bradley-Terry Model
Heejong Bong, Wanshan Li, Shamindra Shrotriya, Alessandro Rinaldo; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3317-3326
Gaussian-Smoothed Optimal Transport: Metric Structure and Statistical Efficiency
Ziv Goldfeld, Kristjan Greenewald; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3327-3337
Learning in Gated Neural Networks
Ashok Makkuva, Sewoong Oh, Sreeram Kannan, Pramod Viswanath; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3338-3348
Validation of Approximate Likelihood and Emulator Models for Computationally Intensive Simulations
Niccolo Dalmasso, Ann Lee, Rafael Izbicki, Taylor Pospisil, Ilmun Kim, Chieh-An Lin; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3349-3361
Fenchel Lifted Networks: A Lagrange Relaxation of Neural Network Training
Fangda Gu, Armin Askari, Laurent El Ghaoui; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3362-3371
Adversarial Robustness Guarantees for Classification with Gaussian Processes
Arno Blaas, Andrea Patane, Luca Laurenti, Luca Cardelli, Marta Kwiatkowska, Stephen Roberts; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3372-3382
Causal inference in degenerate systems: An impossibility result
Yue Wang, Linbo Wang; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3383-3392
ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations
Ksenia Korovina, Sailun Xu, Kirthevasan Kandasamy, Willie Neiswanger, Barnabas Poczos, Jeff Schneider, Eric Xing; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3393-3403
Local Differential Privacy for Sampling
Hisham Husain, Borja Balle, Zac Cranko, Richard Nock; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3404-3413
Learning Sparse Nonparametric DAGs
Xun Zheng, Chen Dan, Bryon Aragam, Pradeep Ravikumar, Eric Xing; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3414-3425
Minimax Rank-$1$ Matrix Factorization
Venkatesh Saligrama, Alexander Olshevsky, Julien Hendrickx; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3426-3436
Context Mover’s Distance & Barycenters: Optimal Transport of Contexts for Building Representations
Sidak Pal Singh, Andreas Hug, Aymeric Dieuleveut, Martin Jaggi; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3437-3449
Data Generation for Neural Programming by Example
Judith Clymo, Haik Manukian, Nathanael Fijalkow, Adria Gascon, Brooks Paige; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3450-3459
An Inverse-free Truncated Rayleigh-Ritz Method for Sparse Generalized Eigenvalue Problem
Yunfeng Cai, Ping Li; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3460-3470
The Gossiping Insert-Eliminate Algorithm for Multi-Agent Bandits
Ronshee Chawla, Abishek Sankararaman, Ayalvadi Ganesh, Sanjay Shakkottai; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3471-3481
Understanding the Effects of Batching in Online Active Learning
Kareem Amin, Corinna Cortes, Giulia DeSalvo, Afshin Rostamizadeh; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3482-3492
Adaptive multi-fidelity optimization with fast learning rates
Côme Fiegel, Victor Gabillon, Michal Valko; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3493-3502
On the interplay between noise and curvature and its effect on optimization and generalization
Valentin Thomas, Fabian Pedregosa, Bart Merriënboer, Pierre-Antoine Manzagol, Yoshua Bengio, Nicolas Le Roux; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3503-3513
A Reduction from Reinforcement Learning to No-Regret Online Learning
Ching-An Cheng, Remi Tachet Combes, Byron Boots, Geoff Gordon; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3514-3524
The Implicit Regularization of Ordinary Least Squares Ensembles
Daniel LeJeune, Hamid Javadi, Richard Baraniuk; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3525-3535
Adaptive Exploration in Linear Contextual Bandit
Botao Hao, Tor Lattimore, Csaba Szepesvari; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3536-3545
A Three Sample Hypothesis Test for Evaluating Generative Models
Casey Meehan, Kamalika Chaudhuri, Sanjoy Dasgupta; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3546-3556
Learning Ising and Potts Models with Latent Variables
Surbhi Goel; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3557-3566
Learning piecewise Lipschitz functions in changing environments
Dravyansh Sharma, Maria-Florina Balcan, Travis Dick; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3567-3577
POPCORN: Partially Observed Prediction Constrained Reinforcement Learning
Joseph Futoma, Michael Hughes, Finale Doshi-Velez; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3578-3588
Optimal Approximation of Doubly Stochastic Matrices
Nikitas Rontsis, Paul Goulart; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3589-3598
The Expressive Power of a Class of Normalizing Flow Models
Zhifeng Kong, Kamalika Chaudhuri; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3599-3609
Screening Data Points in Empirical Risk Minimization via Ellipsoidal Regions and Safe Loss Functions
Grégoire Mialon, Julien Mairal, Alexandre d’Aspremont; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3610-3620
An Empirical Study of Stochastic Gradient Descent with Structured Covariance Noise
Yeming Wen, Kevin Luk, Maxime Gazeau, Guodong Zhang, Harris Chan, Jimmy Ba; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3621-3631
Amortized Inference of Variational Bounds for Learning Noisy-OR
Yiming Yan, Melissa Ailem, Fei Sha; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3632-3641
Gain with no Pain: Efficiency of Kernel-PCA by Nyström Sampling
Nicholas Sterge, Bharath Sriperumbudur, Lorenzo Rosasco, Alessandro Rudi; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3642-3652
Logistic regression with peer-group effects via inference in higher-order Ising models
Constantinos Daskalakis, Nishanth Dikkala, Ioannis Panageas; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3653-3663
An Asymptotic Rate for the LASSO Loss
Cynthia Rush; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3664-3673
Constructing a provably adversarially-robust classifier from a high accuracy one
Grzegorz Gluch, Rüdiger Urbanke; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3674-3684
Distributed, partially collapsed MCMC for Bayesian Nonparametrics
Kumar Avinava Dubey, Michael Zhang, Eric Xing, Sinead Williamson; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3685-3695
Quantized Frank-Wolfe: Faster Optimization, Lower Communication, and Projection Free
Mingrui Zhang, Lin Chen, Aryan Mokhtari, Hamed Hassani, Amin Karbasi; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3696-3706
A Farewell to Arms: Sequential Reward Maximization on a Budget with a Giving Up Option
P Sharoff, Nishant Mehta, Ravi Ganti; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3707-3716
Prophets, Secretaries, and Maximizing the Probability of Choosing the Best
Hossein Esfandiari, MohammadTaghi Hajiaghayi, Brendan Lucier, Michael Mitzenmacher; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3717-3727
A Wasserstein Minimum Velocity Approach to Learning Unnormalized Models
Ziyu Wang, Shuyu Cheng, Li Yueru, Jun Zhu, Bo Zhang; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3728-3738
Sharp Asymptotics and Optimal Performance for Inference in Binary Models
Hossein Taheri, Ramtin Pedarsani, Christos Thrampoulidis; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3739-3749
A Theoretical Case Study of Structured Variational Inference for Community Detection
Mingzhang Yin, Y. X. Rachel Wang, Purnamrita Sarkar; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3750-3761
Orthogonal Gradient Descent for Continual Learning
Mehrdad Farajtabar, Navid Azizan, Alex Mott, Ang Li; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3762-3773
Hamiltonian Monte Carlo Swindles
Dan Piponi, Matthew Hoffman, Pavel Sountsov; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3774-3783
A single algorithm for both restless and rested rotting bandits
Julien Seznec, Pierre Menard, Alessandro Lazaric, Michal Valko; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3784-3794
Adversarial Robustness of Flow-Based Generative Models
Phillip Pope, Yogesh Balaji, Soheil Feizi; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3795-3805
The Power of Batching in Multiple Hypothesis Testing
Tijana Zrnic, Daniel Jiang, Aaditya Ramdas, Michael Jordan; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3806-3815
Adversarial Risk Bounds through Sparsity based Compression
Emilio Balda, Niklas Koep, Arash Behboodi, Rudolf Mathar; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3816-3825
Learning spectrograms with convolutional spectral kernels
Zheyang Shen, Markus Heinonen, Samuel Kaski; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3826-3836
Federated Heavy Hitters Discovery with Differential Privacy
Wennan Zhu, Peter Kairouz, Brendan McMahan, Haicheng Sun, Wei Li; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3837-3847
Online Batch Decision-Making with High-Dimensional Covariates
Chi-Hua Wang, Guang Cheng; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3848-3857
Sample Complexity of Estimating the Policy Gradient for Nearly Deterministic Dynamical Systems
Osbert Bastani; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3858-3869
Scalable Gradients for Stochastic Differential Equations
Xuechen Li, Ting-Kam Leonard Wong, Ricky T. Q. Chen, David Duvenaud; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3870-3882
Understanding the Intrinsic Robustness of Image Distributions using Conditional Generative Models
Xiao Zhang, Jinghui Chen, Quanquan Gu, David Evans; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3883-3893
Uncertainty Quantification for Deep Context-Aware Mobile Activity Recognition and Unknown Context Discovery
Zepeng Huo, Arash PakBin, Xiaohan Chen, Nathan Hurley, Ye Yuan, Xiaoning Qian, Zhangyang Wang, Shuai Huang, Bobak Mortazavi; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3894-3904
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Learnable Bernoulli Dropout for Bayesian Deep Learning
Shahin Boluki, Randy Ardywibowo, Siamak Zamani Dadaneh, Mingyuan Zhou, Xiaoning Qian; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3905-3916
General Identification of Dynamic Treatment Regimes Under Interference
Eli Sherman, David Arbour, Ilya Shpitser; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3917-3927
Gaussian Sketching yields a J-L Lemma in RKHS
Samory Kpotufe, Bharath Sriperumbudur; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3928-3937
Wasserstein Smoothing: Certified Robustness against Wasserstein Adversarial Attacks
Alexander Levine, Soheil Feizi; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3938-3947
Asymptotically Efficient Off-Policy Evaluation for Tabular Reinforcement Learning
Ming Yin, Yu-Xiang Wang; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3948-3958
Learning Dynamic Hierarchical Topic Graph with Graph Convolutional Network for Document Classification
Zhengjue Wang, Chaojie Wang, Hao Zhang, Zhibin Duan, Mingyuan Zhou, Bo Chen; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3959-3969
Differentiable Causal Backdoor Discovery
Limor Gultchin, Matt Kusner, Varun Kanade, Ricardo Silva; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3970-3979
Stochastic Recursive Variance-Reduced Cubic Regularization Methods
Dongruo Zhou, Quanquan Gu; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3980-3990
Better Long-Range Dependency By Bootstrapping A Mutual Information Regularizer
Yanshuai Cao, Peng Xu; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:3991-4001
On the Completeness of Causal Discovery in the Presence of Latent Confounding with Tiered Background Knowledge
Bryan Andrews, Peter Spirtes, Gregory F. Cooper; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4002-4011
One Sample Stochastic Frank-Wolfe
Mingrui Zhang, Zebang Shen, Aryan Mokhtari, Hamed Hassani, Amin Karbasi; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4012-4023
Convex Geometry of Two-Layer ReLU Networks: Implicit Autoencoding and Interpretable Models
Tolga Ergen, Mert Pilanci; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4024-4033
A Robust Univariate Mean Estimator is All You Need
Adarsh Prasad, Sivaraman Balakrishnan, Pradeep Ravikumar; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4034-4044
Patient-Specific Effects of Medication Using Latent Force Models with Gaussian Processes
Li-Fang Cheng, Bianca Dumitrascu, Michael Zhang, Corey Chivers, Michael Draugelis, Kai Li, Barbara Engelhardt; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4045-4055
Robust Variational Autoencoders for Outlier Detection and Repair of Mixed-Type Data
Simao Eduardo, Alfredo Nazabal, Christopher K. I. Williams, Charles Sutton; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4056-4066
Error bounds in estimating the out-of-sample prediction error using leave-one-out cross validation in high-dimensions
Kamiar Rahnama Rad, Wenda Zhou, Arian Maleki; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4067-4077
A Diversity-aware Model for Majority Vote Ensemble Accuracy
Bob Durrant, Nick Lim; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4078-4087
Scaling up Kernel Ridge Regression via Locality Sensitive Hashing
Amir Zandieh, Navid Nouri, Ameya Velingker, Michael Kapralov, Ilya Razenshteyn; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4088-4097
Ordering-Based Causal Structure Learning in the Presence of Latent Variables
Daniel Bernstein, Basil Saeed, Chandler Squires, Caroline Uhler; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4098-4108
Budget Learning via Bracketing
Durmus Alp Emre Acar, Aditya Gangrade, Venkatesh Saligrama; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4109-4119
Optimal Algorithms for Multiplayer Multi-Armed Bandits
PO-AN WANG, Alexandre Proutiere, Kaito Ariu, Yassir Jedra, Alessio Russo; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4120-4129
AP-Perf: Incorporating Generic Performance Metrics in Differentiable Learning
Rizal Fathony, Zico Kolter; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4130-4140
Optimal Deterministic Coresets for Ridge Regression
Praneeth Kacham, David Woodruff; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4141-4150
Expressiveness and Learning of Hidden Quantum Markov Models
Sandesh Adhikary, Siddarth Srinivasan, Geoff Gordon, Byron Boots; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4151-4161
Solving the Robust Matrix Completion Problem via a System of Nonlinear Equations
Yunfeng Cai, Ping Li; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4162-4172
Explicit Mean-Square Error Bounds for Monte-Carlo and Linear Stochastic Approximation
Shuhang Chen, Adithya Devraj, Ana Busic, Sean Meyn; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4173-4183
Stochastic Neural Network with Kronecker Flow
Chin-Wei Huang, Ahmed Touati, Pascal Vincent, Gintare Karolina Dziugaite, Alexandre Lacoste, Aaron Courville; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4184-4194
Fair Correlation Clustering
Sara Ahmadian, Alessandro Epasto, Ravi Kumar, Mohammad Mahdian; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4195-4205
Towards Competitive N-gram Smoothing
Moein Falahatgar, Mesrob Ohannessian, Alon Orlitsky, Venkatadheeraj Pichapati; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4206-4215
Multi-level Gaussian Graphical Models Conditional on Covariates
Gi Bum Kim, Seyoung Kim; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4216-4225
Semi-Modular Inference: enhanced learning in multi-modular models by tempering the influence of components
Christian Carmona, Geoff Nicholls; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4226-4235
Invertible Generative Modeling using Linear Rational Splines
Hadi Mohaghegh Dolatabadi, Sarah Erfani, Christopher Leckie; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4236-4246
LdSM: Logarithm-depth Streaming Multi-label Decision Trees
Maryam Majzoubi, Anna Choromanska; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4247-4257
Prior-aware Composition Inference for Spectral Topic Models
Moontae Lee, David Bindel, David Mimno; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4258-4268
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Variational Optimization on Lie Groups, with Examples of Leading (Generalized) Eigenvalue Problems
Molei Tao, Tomoki Ohsawa; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4269-4280
Best-item Learning in Random Utility Models with Subset Choices
Aadirupa Saha, Aditya Gopalan; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4281-4291
Regularized Autoencoders via Relaxed Injective Probability Flow
Abhishek Kumar, Ben Poole, Kevin Murphy; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4292-4301
Stochastic Variance-Reduced Algorithms for PCA with Arbitrary Mini-Batch Sizes
Cheolmin Kim, Diego Klabjan; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4302-4312
Gradient Descent with Early Stopping is Provably Robust to Label Noise for Overparameterized Neural Networks
Mingchen Li, Mahdi Soltanolkotabi, Samet Oymak; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4313-4324
Scalable Nonparametric Factorization for High-Order Interaction Events
Zhimeng Pan, Zheng Wang, Shandian Zhe; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4325-4335
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Gaussianization Flows
Chenlin Meng, Yang Song, Jiaming Song, Stefano Ermon; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4336-4345
Adaptive, Distribution-Free Prediction Intervals for Deep Networks
Danijel Kivaranovic, Kory D. Johnson, Hannes Leeb; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4346-4356
A Distributional Analysis of Sampling-Based Reinforcement Learning Algorithms
Philip Amortila, Doina Precup, Prakash Panangaden, Marc G. Bellemare; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4357-4366
Automatic Differentiation of Sketched Regression
Hang Liao, Barak A. Pearlmutter, Vamsi K. Potluru, David P. Woodruff; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4367-4376
Sublinear Optimal Policy Value Estimation in Contextual Bandits
Weihao Kong, Emma Brunskill, Gregory Valiant; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4377-4387
Budget-Constrained Bandits over General Cost and Reward Distributions
Semih Cayci, Atilla Eryilmaz, R Srikant; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4388-4398
Measuring Mutual Information Between All Pairs of Variables in Subquadratic Complexity
Mohsen Ferdosi, Arash Gholamidavoodi, Hosein Mohimani; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4399-4409
Online Continuous DR-Submodular Maximization with Long-Term Budget Constraints
Omid Sadeghi, Maryam Fazel; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4410-4419
Prediction Focused Topic Models via Feature Selection
Jason Ren, Russell Kunes, Finale Doshi-Velez; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4420-4429
Accelerated Factored Gradient Descent for Low-Rank Matrix Factorization
Dongruo Zhou, Yuan Cao, Quanquan Gu; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4430-4440
Structured Conditional Continuous Normalizing Flows for Efficient Amortized Inference in Graphical Models
Christian Weilbach, Boyan Beronov, Frank Wood, William Harvey; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4441-4451
Graph Coarsening with Preserved Spectral Properties
Yu Jin, Andreas Loukas, Joseph JaJa; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4452-4462
A Theoretical and Practical Framework for Regression and Classification from Truncated Samples
Andrew Ilyas, Emmanouil Zampetakis, Constantinos Daskalakis; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4463-4473
Permutation Invariant Graph Generation via Score-Based Generative Modeling
Chenhao Niu, Yang Song, Jiaming Song, Shengjia Zhao, Aditya Grover, Stefano Ermon; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4474-4484
Finite-Time Analysis of Decentralized Temporal-Difference Learning with Linear Function Approximation
Jun Sun, Gang Wang, Georgios B. Giannakis, Qinmin Yang, Zaiyue Yang; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4485-4495
Multi-attribute Bayesian optimization with interactive preference learning
Raul Astudillo, Peter Frazier; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4496-4507
On the Sample Complexity of Learning Sum-Product Networks
Ishaq Aden-Ali, Hassan Ashtiani; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4508-4518
Tighter Theory for Local SGD on Identical and Heterogeneous Data
Ahmed Khaled, Konstantin Mishchenko, Peter Richtarik; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4519-4529
Approximate Cross-validation: Guarantees for Model Assessment and Selection
Ashia Wilson, Maximilian Kasy, Lester Mackey; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4530-4540
On Minimax Optimality of GANs for Robust Mean Estimation
Kaiwen Wu, Gavin Weiguang Ding, Ruitong Huang, Yaoliang Yu; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4541-4551
Auditing ML Models for Individual Bias and Unfairness
Songkai Xue, Mikhail Yurochkin, Yuekai Sun; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4552-4562
Stein Variational Inference for Discrete Distributions
Jun Han, Fan Ding, Xianglong Liu, Lorenzo Torresani, Jian Peng, Qiang Liu; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4563-4572
Revisiting Stochastic Extragradient
Konstantin Mishchenko, Dmitry Kovalev, Egor Shulgin, Peter Richtarik, Yura Malitsky; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4573-4582
A Framework for Sample Efficient Interval Estimation with Control Variates
Shengjia Zhao, Christopher Yeh, Stefano Ermon; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4583-4592
Nonmyopic Gaussian Process Optimization with Macro-Actions
Dmitrii Kharkovskii, Chun Kai Ling, Bryan Kian Hsiang Low; Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:4593-4604
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