Learning Theory

Online Learning in Dynamically Changing Environments COLT 2023 Online Learning in Stackelberg Games with an Omniscient Follower ICML 2023 Online Learning with Feedback Graphs: The True Shape of Regret ICML 2023 Online (Multinomial) Logistic Bandit: Improved Regret and Constant Computation Cost NeurIPS 2023 Online Pricing for Multi-User Multi-Item Markets NeurIPS 2023 Online Reinforcement Learning in Stochastic Continuous-Time Systems COLT 2023 Online Reinforcement Learning with Uncertain Episode Lengths AAAI 2023 On Masked Pre-training and the Marginal Likelihood NeurIPS 2023 On Model Selection Consistency of Lasso for High-Dimensional Ising Models AISTATS 2023 On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology ICML 2023 On Proper Learnability between Average- and Worst-case Robustness NeurIPS 2023 On “Scientific Debt” in NLP: A Case for More Rigour in Language Model Pre-Training Research ACL 2023 On Single-Index Models beyond Gaussian Data NeurIPS 2023 On Solution Functions of Optimization: Universal Approximation and Covering Number Bounds AAAI 2023 On student-teacher deviations in distillation: does it pay to disobey? NeurIPS 2023 On Testing and Learning Quantum Junta Channels COLT 2023 On the Asymptotic Learning Curves of Kernel Ridge Regression under Power-law Decay NeurIPS 2023 On the bias of K-fold cross validation with stable learners AISTATS 2023 On the Capacity Limits of Privileged ERM AISTATS 2023 On the Challenges of Using Black-Box APIs for Toxicity Evaluation in Research EMNLP 2023 On the complexity of finding stationary points of smooth functions in one dimension ALT 2023 On the Complexity of Multi-Agent Decision Making: From Learning in Games to Partial Monitoring COLT 2023 On the Complexity of PAC Learning in Hilbert Spaces AAAI 2023 On the Complexity of Representation Learning in Contextual Linear Bandits AISTATS 2023 On the Connection between Invariant Learning and Adversarial Training for Out-of-Distribution Generalization AAAI 2023