minimax lower bound

The optimality of kernel classifiers in Sobolev space ICLR 2024 Transfer Learning for Latent Variable Network Models NeurIPS 2024 A Tale of Sampling and Estimation in Discounted Reinforcement Learning AISTATS 2023 Causal Bandits for Linear Structural Equation Models JMLR 2023 Fine-Grained Distribution-Dependent Learning Curves COLT 2023 Improved Bounds for Multi-task Learning with Trace Norm Regularization COLT 2023 Optimal testing using combined test statistics across independent studies NeurIPS 2023 Towards Theoretical Understanding of Inverse Reinforcement Learning ICML 2023 Unified Lower Bounds for Interactive High-dimensional Estimation under Information Constraints NeurIPS 2023 ℓ_∞-Bounds of the MLE in the BTL Model under General Comparison Graphs UAI 2022 Bridging Central and Local Differential Privacy in Data Acquisition Mechanisms NeurIPS 2022 Learning to Control Linear Systems can be Hard COLT 2022 Optimal and instance-dependent guarantees for Markovian linear stochastic approximation COLT 2022 Two-Sample Testing on Ranked Preference Data and the Role of Modeling Assumptions JMLR 2022 Uniform deconvolution for Poisson Point Processes JMLR 2022 Episodic Reinforcement Learning in Finite MDPs: Minimax Lower Bounds Revisited ALT 2021 Minimax Estimation of Laplacian Constrained Precision Matrices AISTATS 2021 Optimal Rates for Nonparametric Density Estimation under Communication Constraints NeurIPS 2021 Provable Benefits of Actor-Critic Methods for Offline Reinforcement Learning NeurIPS 2021 Sharp Impossibility Results for Hyper-graph Testing NeurIPS 2021 Learning discrete distributions with infinite support NeurIPS 2020 Minimax Lower Bounds for Transfer Learning with Linear and One-hidden Layer Neural Networks NeurIPS 2020 Minimax-Optimal Off-Policy Evaluation with Linear Function Approximation ICML 2020 Optimal Estimation of Sparse Topic Models JMLR 2020 A Learning Theory of Ranking Aggregation AISTATS 2017