hypothesis class

A Novel Data-Dependent Learning Paradigm for Large Hypothesis Classes ALT 2026 Generation from Noisy Examples ICML 2025 Proofs as Explanations: Short Certificates for Reliable Predictions COLT 2025 Active Learning with Simple Questions COLT 2024 Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures AISTATS 2024 Open Problem: Can Local Regularization Learn All Multiclass Problems? COLT 2024 The Real Price of Bandit Information in Multiclass Classification COLT 2024 The sample complexity of multi-distribution learning COLT 2024 When Is Inductive Inference Possible? NeurIPS 2024 Find a witness or shatter: the landscape of computable PAC learning. COLT 2023 In-Context Learning Creates Task Vectors EMNLP 2023 Universal Rates for Multiclass Learning COLT 2023 When do Minimax-fair Learning and Empirical Risk Minimization Coincide? ICML 2023 Generalization Bounds with Minimal Dependency on Hypothesis Class via Distributionally Robust Optimization NeurIPS 2022 On Optimal Learning Under Targeted Data Poisoning NeurIPS 2022 Non-uniform Consistency of Online Learning with Random Sampling ALT 2021 Approximate is Good Enough: Probabilistic Variants of Dimensional and Margin Complexity COLT 2020 Online Multitask Learning with Long-Term Memory NeurIPS 2020 Open Problem: Model Selection for Contextual Bandits COLT 2020 Reducing Adversarially Robust Learning to Non-Robust PAC Learning NeurIPS 2020 Learning Rules-First Classifiers AISTATS 2019 Preference-Based Batch and Sequential Teaching: Towards a Unified View of Models NeurIPS 2019 Teaching a black-box learner ICML 2019 Mixing Implies Lower Bounds for Space Bounded Learning COLT 2017 Minimax Analysis of Active Learning JMLR 2015