information-theoretic lower bound

Testing for a Hidden Geometry in Random Graphs COLT 2026 Constrained Pareto Set Identification with Bandit Feedback ICML 2025 Density-Dependent Group Testing AISTATS 2025 Linear Bandits on Ellipsoids: Minimax Optimal Algorithms COLT 2025 Assouad, Fano, and Le Cam with Interaction: A Unifying Lower Bound Framework and Characterization for Bandit Learnability NeurIPS 2024 Clustering Items From Adaptively Collected Inconsistent Feedback AISTATS 2024 Multi-View Stochastic Block Models ICML 2024 Optimal Clustering with Bandit Feedback JMLR 2024 Pure Exploration in Bandits with Linear Constraints AISTATS 2024 Semi-Supervised Sparse Gaussian Classification: Provable Benefits of Unlabeled Data NeurIPS 2024 The Limits of Transfer Reinforcement Learning with Latent Low-rank Structure NeurIPS 2024 A Tighter Problem-Dependent Regret Bound for Risk-Sensitive Reinforcement Learning AISTATS 2023 Communication-Constrained Bandits under Additive Gaussian Noise ICML 2023 Distributed Linear Bandits under Communication Constraints ICML 2023 Minimax Optimal Kernel Operator Learning via Multilevel Training ICLR 2023 Nested Elimination: A Simple Algorithm for Best-Item Identification From Choice-Based Feedback ICML 2023 On the Saturation Effect of Kernel Ridge Regression ICLR 2023 Provably Efficient Offline Reinforcement Learning with Perturbed Data Sources ICML 2023 On the inability of Gaussian process regression to optimally learn compositional functions NeurIPS 2022 Optimal Mean Estimation without a Variance COLT 2022 Statistical and Computational Phase Transitions in Group Testing COLT 2022 Model-Free Reinforcement Learning: from Clipped Pseudo-Regret to Sample Complexity ICML 2021 The Complexity of Sparse Tensor PCA NeurIPS 2021 Disagreement-Based Combinatorial Pure Exploration: Sample Complexity Bounds and an Efficient Algorithm COLT 2019 On Learning Invariant Representations for Domain Adaptation ICML 2019