Policy Learning

Privacy Preserving Adaptive Experiment Design ICML 2024 Privacy-Preserving Decentralized Actor-Critic for Cooperative Multi-Agent Reinforcement Learning AISTATS 2024 Privacy-Preserving UCB Decision Process Verification via zk-SNARKs IJCAI 2024 Probabilistic Constrained Reinforcement Learning with Formal Interpretability ICML 2024 Provable Benefits of Multi-task RL under Non-Markovian Decision Making Processes ICLR 2024 Provable Policy Gradient Methods for Average-Reward Markov Potential Games AISTATS 2024 Provably and Practically Efficient Adversarial Imitation Learning with General Function Approximation NeurIPS 2024 Provably Efficient Long-Horizon Exploration in Monte Carlo Tree Search through State Occupancy Regularization ICML 2024 Provably Efficient Reinforcement Learning with Multinomial Logit Function Approximation NeurIPS 2024 Provably Robust DPO: Aligning Language Models with Noisy Feedback ICML 2024 Pursuing Overall Welfare in Federated Learning through Sequential Decision Making ICML 2024 Q-Probe: A Lightweight Approach to Reward Maximization for Language Models ICML 2024 Q-Star Meets Scalable Posterior Sampling: Bridging Theory and Practice via HyperAgent ICML 2024 Query-Policy Misalignment in Preference-Based Reinforcement Learning ICLR 2024 Randomized Exploration for Reinforcement Learning with Multinomial Logistic Function Approximation NeurIPS 2024 RA-PbRL: Provably Efficient Risk-Aware Preference-Based Reinforcement Learning NeurIPS 2024 Rate-Optimal Policy Optimization for Linear Markov Decision Processes ICML 2024 Rating-Based Reinforcement Learning AAAI 2024 REBEL: Reinforcement Learning via Regressing Relative Rewards NeurIPS 2024 Recent Advancements in Inverse Reinforcement Learning AAAI 2024 Reclaiming the Source of Programmatic Policies: Programmatic versus Latent Spaces ICLR 2024 Recurrent Reinforcement Learning with Memoroids NeurIPS 2024 Reflective Policy Optimization ICML 2024 Regret Analysis of Policy Gradient Algorithm for Infinite Horizon Average Reward Markov Decision Processes AAAI 2024 Reinforcement Learning from Reachability Specifications: PAC Guarantees with Expected Conditional Distance ICML 2024