Methods

On the Effect of Auxiliary Tasks on Representation Dynamics AISTATS 2021 On the Estimation Bias in Double Q-Learning NeurIPS 2021 On the Expressivity of Markov Reward NeurIPS 2021 On the Linear Convergence of Policy Gradient Methods for Finite MDPs AISTATS 2021 On the Model-Based Stochastic Value Gradient for Continuous Reinforcement Learning L4DC 2021 On the Optimality of Batch Policy Optimization Algorithms ICML 2021 On the role of planning in model-based deep reinforcement learning ICLR 2021 On the Stability of Random Matrix Product with Markovian Noise: Application to Linear Stochastic Approximation and TD Learning COLT 2021 On the Theory of Policy Gradient Methods: Optimality, Approximation, and Distribution Shift JMLR 2021 On the Theory of Reinforcement Learning with Once-per-Episode Feedback NeurIPS 2021 OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning ICLR 2021 OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation ICML 2021 Optimal Off-Policy Evaluation from Multiple Logging Policies ICML 2021 Optimal Uniform OPE and Model-based Offline Reinforcement Learning in Time-Homogeneous, Reward-Free and Task-Agnostic Settings NeurIPS 2021 Optimistic Agent: Accurate Graph-Based Value Estimation for More Successful Visual Navigation WACV 2021 Optimizing Percentile Criterion using Robust MDPs AISTATS 2021 Oracle-Efficient Regret Minimization in Factored MDPs with Unknown Structure NeurIPS 2021 Ordering-Based Causal Discovery with Reinforcement Learning IJCAI 2021 Outcome-Driven Reinforcement Learning via Variational Inference NeurIPS 2021 Parallel Droplet Control in MEDA Biochips using Multi-Agent Reinforcement Learning ICML 2021 Parametrized Quantum Policies for Reinforcement Learning NeurIPS 2021 Partial Policy Iteration for L1-Robust Markov Decision Processes JMLR 2021 PatchMatch-RL: Deep MVS With Pixelwise Depth, Normal, and Visibility ICCV 2021 Pattern-enhanced Contrastive Policy Learning Network for Sequential Recommendation IJCAI 2021 PC-MLP: Model-based Reinforcement Learning with Policy Cover Guided Exploration ICML 2021