AISTATS

Keyphrases

Publications

2023

Lev Telyatnikov, Simone Scardapane
EGG-GAE: scalable graph neural networks for tabular data imputation. AISTATS (2023)
Anirban Samaddar, Sandeep Madireddy, Prasanna Balaprakash, Taps Maiti, Gustavo de los Campos, Ian Fischer
Sparsity-Inducing Categorical Prior Improves Robustness of the Information Bottleneck. AISTATS (2023)
Nathan Kallus, Miruna Oprescu
Robust and Agnostic Learning of Conditional Distributional Treatment Effects. AISTATS (2023)
Srshti Putcha, Christopher Nemeth, Paul Fearnhead
Preferential Subsampling for Stochastic Gradient Langevin Dynamics. AISTATS (2023)
Tamara A. Pereira, Erik Nascimento, Lucas E. Resck, Diego Mesquita, Amauri A. Souza
Distill n' Explain: explaining graph neural networks using simple surrogates. AISTATS (2023)
Chandramauli Chakraborty, Sayan Paul, Saptarshi Chakraborty, Swagatam Das
Regularization. AISTATS (2023)
Jen Ning Lim, Sebastian J. Vollmer, Lorenz Wolf, Andrew Duncan
Energy-Based Models for Functional Data using Path Measure Tilting. AISTATS (2023)
Helmuth J. Naumer, Farzad Kamalabadi
Dimensionality Collapse: Optimal Measurement Selection for Low-Error Infinite-Horizon Forecasting. AISTATS (2023)
Hideaki Ishibashi, Masayuki Karasuyama, Ichiro Takeuchi, Hideitsu Hino
A stopping criterion for Bayesian optimization by the gap of expected minimum simple regrets. AISTATS (2023)
Antonio Orvieto, Anant Raj, Hans Kersting, Francis R. Bach
Explicit Regularization in Overparametrized Models via Noise Injection. AISTATS (2023)
Hadrien Hendrikx
A principled framework for the design and analysis of token algorithms. AISTATS (2023)
Yikai Zhang, Jiahe Lin, Fengpei Li, Yeshaya Adler, Kashif Rasul, Anderson Schneider, Yuriy Nevmyvaka
Risk Bounds on Aleatoric Uncertainty Recovery. AISTATS (2023)
Samuel Holt, Alihan Hüyük, Zhaozhi Qian, Hao Sun, Mihaela van der Schaar
Neural Laplace Control for Continuous-time Delayed Systems. AISTATS (2023)
Pierre Gaillard, Aadirupa Saha, Soham Dan
One Arrow, Two Kills: A Unified Framework for Achieving Optimal Regret Guarantees in Sleeping Bandits. AISTATS (2023)
Dan Meller, Nicolas Berkouk
Singular Value Representation: A New Graph Perspective On Neural Networks. AISTATS (2023)
Yulai Zhao, Jianshu Chen, Simon S. Du
Blessing of Class Diversity in Pre-training. AISTATS (2023)
Anass Aghbalou, Anne Sabourin, François Portier
On the bias of K-fold cross validation with stable learners. AISTATS (2023)
Daniel P. Jeong, Seyoung Kim
Factorial SDE for Multi-Output Gaussian Process Regression. AISTATS (2023)
Dheeraj Baby, Yu-Xiang Wang
Second Order Path Variationals in Non-Stationary Online Learning. AISTATS (2023)
Daniel Goldfarb, Paul Hand
Analysis of Catastrophic Forgetting for Random Orthogonal Transformation Tasks in the Overparameterized Regime. AISTATS (2023)
Prashant Trivedi, Nandyala Hemachandra
Multi-Agent congestion cost minimization with linear function approximations. AISTATS (2023)
Yiding Chen, Xuezhou Zhang, Kaiqing Zhang, Mengdi Wang, Xiaojin Zhu
Byzantine-Robust Online and Offline Distributed Reinforcement Learning. AISTATS (2023)
Elvis Dohmatob, Chuan Guo, Morgane Goibert
Origins of Low-Dimensional Adversarial Perturbations. AISTATS (2023)
Lingxiao Wang, Boxin Zhao, Mladen Kolar
Differentially Private Matrix Completion through Low-rank Matrix Factorization. AISTATS (2023)
Yassir Jedra, Junghyun Lee, Alexandre Proutière, Se-Young Yun
Nearly Optimal Latent State Decoding in Block MDPs. AISTATS (2023)
Dennis Wei, Haoze Wu, Min Wu, Pin-Yu Chen, Clark W. Barrett, Eitan Farchi
Convex Bounds on the Softmax Function with Applications to Robustness Verification. AISTATS (2023)
Hongru Yang, Zhangyang Wang
On the Neural Tangent Kernel Analysis of Randomly Pruned Neural Networks. AISTATS (2023)
Osman Ali Mian, David Kaltenpoth, Michael Kamp, Jilles Vreeken
Nothing but Regrets - Privacy-Preserving Federated Causal Discovery. AISTATS (2023)
Sulin Liu, Qing Feng, David Eriksson, Benjamin Letham, Eytan Bakshy
Sparse Bayesian optimization. AISTATS (2023)
Thomas M. McDonald, Magnus Ross, Michael T. Smith, Mauricio A. Álvarez
Nonparametric Gaussian Process Covariances via Multidimensional Convolutions. AISTATS (2023)
Hossein Taheri, Christos Thrampoulidis
On Generalization of Decentralized Learning with Separable Data. AISTATS (2023)
Shalev Shaer, Gal Maman, Yaniv Romano
Model-X Sequential Testing for Conditional Independence via Testing by Betting. AISTATS (2023)
Tina Behnia, Ganesh Ramachandra Kini, Vala Vakilian, Christos Thrampoulidis
On the Implicit Geometry of Cross-Entropy Parameterizations for Label-Imbalanced Data. AISTATS (2023)
Charles K. Assaad, Imad Ez-zejjari, Lei Zan
Root Cause Identification for Collective Anomalies in Time Series given an Acyclic Summary Causal Graph with Loops. AISTATS (2023)
Zhichao Wang, Yizhe Zhu
Overparameterized Random Feature Regression with Nearly Orthogonal Data. AISTATS (2023)
Jia-Wei Shan, Peng Zhao, Zhi-Hua Zhou
Beyond Performative Prediction: Open-environment Learning with Presence of Corruptions. AISTATS (2023)
Vincent Plassier, Eric Moulines, Alain Durmus
Federated Averaging Langevin Dynamics: Toward a unified theory and new algorithms. AISTATS (2023)
Xun Qian, Hanze Dong, Tong Zhang, Peter Richtárik
Catalyst Acceleration of Error Compensated Methods Leads to Better Communication Complexity. AISTATS (2023)
Namrata Deka, Danica J. Sutherland
MMD-B-Fair: Learning Fair Representations with Statistical Testing. AISTATS (2023)
Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang, Vahab Mirrokni
Pricing against a Budget and ROI Constrained Buyer. AISTATS (2023)
Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric
On the Complexity of Representation Learning in Contextual Linear Bandits. AISTATS (2023)
Emilio Dorigatti, Benjamin Schubert, Bernd Bischl, David Rügamer
Frequentist Uncertainty Quantification in Semi-Structured Neural Networks. AISTATS (2023)
Shiv Shankar, Ritwik Sinha, Saayan Mitra, Moumita Sinha, Madalina Fiterau
Direct Inference of Effect of Treatment (DIET) for a Cookieless World. AISTATS (2023)
Michael Sucker, Peter Ochs
PAC-Bayesian Learning of Optimization Algorithms. AISTATS (2023)
Rosanne Turner, Peter Grunwald
Safe Sequential Testing and Effect Estimation in Stratified Count Data. AISTATS (2023)
Matthäus Kleindessner, Michele Donini, Chris Russell, Muhammad Bilal Zafar
Efficient fair PCA for fair representation learning. AISTATS (2023)
Charles Marx, Youngsuk Park, Hilaf Hasson, Yuyang Wang, Stefano Ermon, Luke Huan
But Are You Sure? An Uncertainty-Aware Perspective on Explainable AI. AISTATS (2023)
Batiste Le Bars, Aurélien Bellet, Marc Tommasi, Erick Lavoie, Anne-Marie Kermarrec
Refined Convergence and Topology Learning for Decentralized SGD with Heterogeneous Data. AISTATS (2023)
Zeju Qiu, Weiyang Liu, Tim Z. Xiao, Zhen Liu, Umang Bhatt, Yucen Luo, Adrian Weller, Bernhard Schölkopf
Iterative Teaching by Data Hallucination. AISTATS (2023)

volume 206, 2023

International Conference on Artificial Intelligence and Statistics, 25-27 April 2023, Palau de Congressos, Valencia, Spain. AISTATS 206 (2023)