Deep RL

Improving Computational Efficiency in Visual Reinforcement Learning via Stored Embeddings NeurIPS 2021 Improving Generalization in Meta-RL with Imaginary Tasks from Latent Dynamics Mixture NeurIPS 2021 Improving Sample Efficiency in Model-Free Reinforcement Learning from Images AAAI 2021 Independence-aware Advantage Estimation IJCAI 2021 Information is Power: Intrinsic Control via Information Capture NeurIPS 2021 Instance-Dependent Complexity of Contextual Bandits and Reinforcement Learning: A Disagreement-Based Perspective COLT 2021 Intelligent and Learning Agents: Four Investigations IJCAI 2021 Interactive Reinforcement Learning for Table Balancing Robot ACL 2021 Inverse Constrained Reinforcement Learning ICML 2021 Inverse Reinforcement Learning with Natural Language Goals AAAI 2021 Investigating vulnerabilities of deep neural policies UAI 2021 Is Bang-Bang Control All You Need? Solving Continuous Control with Bernoulli Policies NeurIPS 2021 Is Pessimism Provably Efficient for Offline RL? ICML 2021 Iterative Amortized Policy Optimization NeurIPS 2021 Iterative Empirical Game Solving via Single Policy Best Response ICLR 2021 Iterative Shrinking for Referring Expression Grounding Using Deep Reinforcement Learning CVPR 2021 Kernel-Based Reinforcement Learning: A Finite-Time Analysis ICML 2021 Keyphrase Generation with Fine-Grained Evaluation-Guided Reinforcement Learning EMNLP 2021 Landmark-Guided Subgoal Generation in Hierarchical Reinforcement Learning NeurIPS 2021 Language Model Augmented Relevance Score ACL 2021 Language Models are Few-Shot Butlers EMNLP 2021 Language Representations for Generalization in Reinforcement Learning ACML 2021 Large Batch Simulation for Deep Reinforcement Learning ICLR 2021 LAU-Net: Latitude Adaptive Upscaling Network for Omnidirectional Image Super-Resolution CVPR 2021 Learning 3-opt heuristics for traveling salesman problem via deep reinforcement learning ACML 2021