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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

Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems JMLR 2020
Convex Programming for Estimation in Nonlinear Recurrent Models JMLR 2020
Minimax Testing of Identity to a Reference Ergodic Markov Chain AISTATS 2020
Minimax Bounds for Structured Prediction Based on Factor Graphs AISTATS 2020
Sample complexity bounds for localized sketching AISTATS 2020
Best-item Learning in Random Utility Models with Subset Choices AISTATS 2020
Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample Complexity NIPS 2020
Planning in Markov Decision Processes with Gap-Dependent Sample Complexity NIPS 2020
Near-Optimal Reinforcement Learning with Self-Play NIPS 2020
Exploiting Higher Order Smoothness in Derivative-free Optimization and Continuous Bandits NIPS 2020
Best Arm Identification in Spectral Bandits IJCAI 2020
Robust guarantees for learning an autoregressive filter ALT 2020
Provably efficient reinforcement learning with linear function approximation COLT 2020
Sample Complexity of Estimating the Policy Gradient for Nearly Deterministic Dynamical Systems AISTATS 2020
Count-Based Exploration with the Successor Representation AAAI 2020
Efficient Algorithms for Learning Revenue-Maximizing Two-Part Tariffs IJCAI 2020
On the Sample Complexity of Learning Sum-Product Networks AISTATS 2020
Robust Policies via Mid-Level Visual Representations: An Experimental Study in Manipulation and Navigation CORL 2020
Reinforcement Learning with Perturbed Rewards AAAI 2020
Data Amplification: Instance-Optimal Property Estimation ICML 2020
Linear-Sample Learning of Low-Rank Distributions NIPS 2020
Learning in Gated Neural Networks AISTATS 2020
How many samples is a good initial point worth in Low-rank Matrix Recovery? NIPS 2020
Providing Uncertainty-Based Advice for Deep Reinforcement Learning Agents (Student Abstract) AAAI 2020
Learning the Globally Optimal Distributed LQ Regulator L4DC 2020