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Reinforcement Learning

2,944 papers

Papers per year

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Papers

Robust Offline Reinforcement Learning with Heavy-Tailed Rewards AISTATS 2024
Prior-dependent analysis of posterior sampling reinforcement learning with function approximation AISTATS 2024
Towards Achieving Sub-linear Regret and Hard Constraint Violation in Model-free RL AISTATS 2024
A Unifying Variational Framework for Gaussian Process Motion Planning AISTATS 2024
Thompson Sampling Itself is Differentially Private AISTATS 2024
A/B Testing and Best-arm Identification for Linear Bandits with Robustness to Non-stationarity AISTATS 2024
Solving General Noisy Inverse Problem via Posterior Sampling: A Policy Gradient Viewpoint AISTATS 2024
Safe and Interpretable Estimation of Optimal Treatment Regimes AISTATS 2024
Online learning in bandits with predicted context AISTATS 2024
MIM-Reasoner: Learning with Theoretical Guarantees for Multiplex Influence Maximization AISTATS 2024
Learning Safety Constraints from Demonstrations with Unknown Rewards AISTATS 2024
Distributionally Robust Off-Dynamics Reinforcement Learning: Provable Efficiency with Linear Function Approximation AISTATS 2024
Policy Evaluation for Reinforcement Learning from Human Feedback: A Sample Complexity Analysis AISTATS 2024
On the Model-Misspecification in Reinforcement Learning AISTATS 2024
Privacy-Constrained Policies via Mutual Information Regularized Policy Gradients AISTATS 2024
Online Learning of Decision Trees with Thompson Sampling AISTATS 2024
Improved Algorithm for Adversarial Linear Mixture MDPs with Bandit Feedback and Unknown Transition AISTATS 2024
Improved Sample Complexity Analysis of Natural Policy Gradient Algorithm with General Parameterization for Infinite Horizon Discounted Reward Markov Decision Processes AISTATS 2024
Don’t Be Pessimistic Too Early: Look K Steps Ahead! AISTATS 2024
Resilient Constrained Reinforcement Learning AISTATS 2024
On learning history-based policies for controlling Markov decision processes AISTATS 2024
Horizon-Free and Instance-Dependent Regret Bounds for Reinforcement Learning with General Function Approximation AISTATS 2024
A Bayesian Learning Algorithm for Unknown Zero-sum Stochastic Games with an Arbitrary Opponent AISTATS 2024
Near-Optimal Policy Optimization for Correlated Equilibrium in General-Sum Markov Games AISTATS 2024
Efficient Variational Sequential Information Control AISTATS 2024