Methods

On the Convergence Rate of Off-Policy Policy Optimization Methods with Density-Ratio Correction AISTATS 2022 On the Convergence Rates of Policy Gradient Methods JMLR 2022 On the Effectiveness of Fine-tuning Versus Meta-reinforcement Learning NeurIPS 2022 On the Effect of Pre-training for Transformer in Different Modality on Offline Reinforcement Learning NeurIPS 2022 On the Expressivity of Markov Reward (Extended Abstract) IJCAI 2022 On the Generalization of Representations in Reinforcement Learning AISTATS 2022 On the Global Convergence Rates of Decentralized Softmax Gradient Play in Markov Potential Games NeurIPS 2022 On the Global Optimum Convergence of Momentum-based Policy Gradient AISTATS 2022 On the Hidden Biases of Policy Mirror Ascent in Continuous Action Spaces ICML 2022 On the (In)Tractability of Reinforcement Learning for LTL Objectives IJCAI 2022 On the Role of Discount Factor in Offline Reinforcement Learning ICML 2022 On the role of overparameterization in off-policy Temporal Difference learning with linear function approximation NeurIPS 2022 On the Sample Complexity of Learning Infinite-horizon Discounted Linear Kernel MDPs ICML 2022 On the Sample Complexity of Stability Constrained Imitation Learning L4DC 2022 On the Statistical Efficiency of Reward-Free Exploration in Non-Linear RL NeurIPS 2022 On Well-posedness and Minimax Optimal Rates of Nonparametric Q-function Estimation in Off-policy Evaluation ICML 2022 Open-Ended Reinforcement Learning with Neural Reward Functions NeurIPS 2022 Operator Splitting Value Iteration NeurIPS 2022 Optimal control of partially observable Markov decision processes with finite linear temporal logic constraints UAI 2022 Optimal Estimation of Policy Gradient via Double Fitted Iteration ICML 2022 Optimal Pointing Sequences in Spacecraft Formation Flying Using Online Planning with Resource Constraints L4DC 2022 Optimal Transport for Stationary Markov Chains via Policy Iteration JMLR 2022 Optimistic Initialization for Exploration in Continuous Control AAAI 2022 Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees NeurIPS 2022 Optimizing Sequential Experimental Design with Deep Reinforcement Learning ICML 2022