Reinforcement Learning

Off-Policy Evaluation via the Regularized Lagrangian NeurIPS 2020 Off-Policy Imitation Learning from Observations NeurIPS 2020 Off-Policy Interval Estimation with Lipschitz Value Iteration NeurIPS 2020 Off-policy Policy Evaluation For Sequential Decisions Under Unobserved Confounding NeurIPS 2020 On Bonus Based Exploration Methods In The Arcade Learning Environment ICLR 2020 On Computation and Generalization of Generative Adversarial Imitation Learning ICLR 2020 One Policy to Control Them All: Shared Modular Policies for Agent-Agnostic Control ICML 2020 One Solution is Not All You Need: Few-Shot Extrapolation via Structured MaxEnt RL NeurIPS 2020 Online Decision Based Visual Tracking via Reinforcement Learning NeurIPS 2020 Online learning with dynamics: A minimax perspective NeurIPS 2020 Online Meta-Critic Learning for Off-Policy Actor-Critic Methods NeurIPS 2020 Online Planning with Lookahead Policies NeurIPS 2020 Only Relevant Information Matters: Filtering Out Noisy Samples To Boost RL IJCAI 2020 On Overfitting and Asymptotic Bias in Batch Reinforcement Learning with Partial Observability (Extended Abstract) IJCAI 2020 On Reward-Free Reinforcement Learning with Linear Function Approximation NeurIPS 2020 On the Convergence of Model Free Learning in Mean Field Games AAAI 2020 On the Convergence of Smooth Regularized Approximate Value Iteration Schemes NeurIPS 2020 On the Expressivity of Neural Networks for Deep Reinforcement Learning ICML 2020 On the Global Convergence Rates of Softmax Policy Gradient Methods ICML 2020 On the Role of Weight Sharing During Deep Option Learning AAAI 2020 On the Stability and Convergence of Robust Adversarial Reinforcement Learning: A Case Study on Linear Quadratic Systems NeurIPS 2020 On the Weaknesses of Reinforcement Learning for Neural Machine Translation ICLR 2020 Optical Non-Line-of-Sight Physics-Based 3D Human Pose Estimation CVPR 2020 Optimal Exploration Algorithm of Multi-Agent Reinforcement Learning Methods (Student Abstract) AAAI 2020 Optimality and Approximation with Policy Gradient Methods in Markov Decision Processes COLT 2020