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sample complexity

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reinforcement learning (4122) pac learning (280) multi-armed bandit (1091) markov decision process (788) learning theory (518) differential privacy (1010) stochastic optimization (1060) neural network (6616) active learning (1295) regret bound (1918)

Papers

Episodic Reinforcement Learning in Finite MDPs: Minimax Lower Bounds Revisited ALT 2021
Adaptive Reward-Free Exploration ALT 2021
Robust learning under clean-label attack COLT 2021
The Sample Complexity of Robust Covariance Testing COLT 2021
Generalizing Complex Hypotheses on Product Distributions: Auctions, Prophet Inequalities, and Pandora’s Problem COLT 2021
Adversarially Robust Learning with Unknown Perturbation Sets COLT 2021
Cautiously Optimistic Policy Optimization and Exploration with Linear Function Approximation COLT 2021
Is Reinforcement Learning More Difficult Than Bandits? A Near-optimal Algorithm Escaping the Curse of Horizon COLT 2021
Testification of Condorcet Winners in dueling bandits UAI 2021
The Sample Complexity of Meta Sparse Regression AISTATS 2021
Efficient Methods for Structured Nonconvex-Nonconcave Min-Max Optimization AISTATS 2021
On the Convergence and Sample Efficiency of Variance-Reduced Policy Gradient Method NIPS 2021
Derivative-Free Policy Optimization for Linear Risk-Sensitive and Robust Control Design: Implicit Regularization and Sample Complexity NIPS 2021
Empirical Risk Minimization in the Non-interactive Local Model of Differential Privacy JMLR 2020
Reward-Free Exploration for Reinforcement Learning ICML 2020
Learning with Good Feature Representations in Bandits and in RL with a Generative Model ICML 2020
Control Frequency Adaptation via Action Persistence in Batch Reinforcement Learning ICML 2020
Near-optimal sample complexity bounds for learning Latent $k-$polytopes and applications to Ad-Mixtures ICML 2020
Private Query Release Assisted by Public Data ICML 2020
Distributed Signal Detection under Communication Constraints COLT 2020
Sample Complexity Bounds for 1-bit Compressive Sensing and Binary Stable Embeddings with Generative Priors ICML 2020
On the Complexity of Proper Distribution-Free Learning of Linear Classifiers ALT 2020
Agnostic $Q$-learning with Function Approximation in Deterministic Systems: Near-Optimal Bounds on Approximation Error and Sample Complexity NIPS 2020
Variance-Reduced Off-Policy TDC Learning: Non-Asymptotic Convergence Analysis NIPS 2020
Online Planning with Lookahead Policies NIPS 2020