sample complexity

1158 papers

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Co-occurring keywords

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

On the Convergence and Sample Complexity Analysis of Deep Q-Networks with $\epsilon$-Greedy Exploration NIPS 2023

On Single-Index Models beyond Gaussian Data NIPS 2023

Feature learning via mean-field Langevin dynamics: classifying sparse parities and beyond NIPS 2023

PAC Learning of Halfspaces with Malicious Noise in Nearly Linear Time AISTATS 2023

Multi-task Representation Learning for Pure Exploration in Bilinear Bandits NIPS 2023

What can a Single Attention Layer Learn? A Study Through the Random Features Lens NIPS 2023

Active representation learning for general task space with applications in robotics NIPS 2023

Information Theoretic Lower Bounds for Information Theoretic Upper Bounds NIPS 2023

Sample Complexity Bounds for Score-Matching: Causal Discovery and Generative Modeling NIPS 2023

Initialization-Dependent Sample Complexity of Linear Predictors and Neural Networks NIPS 2023

Robust Mean Estimation Without Moments for Symmetric Distributions NIPS 2023

Stochastic Approximation Approaches to Group Distributionally Robust Optimization NIPS 2023

Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample Complexity JMLR 2023

An $\varepsilon$-Best-Arm Identification Algorithm for Fixed-Confidence and Beyond NIPS 2023

Multi-User Reinforcement Learning with Low Rank Rewards ICML 2023

Towards Theoretical Understanding of Inverse Reinforcement Learning ICML 2023

Prometheus: Taming Sample and Communication Complexities in Constrained Decentralized Stochastic Bilevel Learning ICML 2023

Near-Optimal Bounds for Learning Gaussian Halfspaces with Random Classification Noise NIPS 2023

Horizon-free Learning for Markov Decision Processes and Games: Stochastically Bounded Rewards and Improved Bounds ICML 2023

Reward-Mixing MDPs with Few Latent Contexts are Learnable ICML 2023

Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice ICML 2023

Stochastic Policy Gradient Methods: Improved Sample Complexity for Fisher-non-degenerate Policies ICML 2023

The Power of Learned Locally Linear Models for Nonlinear Policy Optimization ICML 2023

Fast Rates for Maximum Entropy Exploration ICML 2023

Lower Bounds for Learning in Revealing POMDPs ICML 2023