Deep RL

On Bonus Based Exploration Methods In The Arcade Learning Environment ICLR 2020 On Computation and Generalization of Generative Adversarial Imitation Learning ICLR 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 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 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 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 Optical Non-Line-of-Sight Physics-Based 3D Human Pose Estimation CVPR 2020 Optimality and Approximation with Policy Gradient Methods in Markov Decision Processes COLT 2020 Optimizing the Factual Correctness of a Summary: A Study of Summarizing Radiology Reports ACL 2020 Option Discovery in the Absence of Rewards with Manifold Analysis ICML 2020 Options of Interest: Temporal Abstraction with Interest Functions AAAI 2020 PADS: Policy-Adapted Sampling for Visual Similarity Learning CVPR 2020 Parameterized Indexed Value Function for Efficient Exploration in Reinforcement Learning AAAI 2020 Periodic Q-Learning L4DC 2020 PFRL: Pose-Free Reinforcement Learning for 6D Pose Estimation CVPR 2020 PixL2R: Guiding Reinforcement Learning Using Natural Language by Mapping Pixels to Rewards CoRL 2020 PlanGAN: Model-based Planning With Sparse Rewards and Multiple Goals NeurIPS 2020 Planning to Explore via Self-Supervised World Models ICML 2020 Planning with Abstract Learned Models While Learning Transferable Subtasks AAAI 2020 Playing Atari with Six Neurons (Extended Abstract) IJCAI 2020 Point-Based Methods for Model Checking in Partially Observable Markov Decision Processes AAAI 2020