Deep RL

Kernel-Based Reinforcement Learning in Robust Markov Decision Processes ICML 2019 Language as an Abstraction for Hierarchical Deep Reinforcement Learning NeurIPS 2019 Language-Driven Temporal Activity Localization: A Semantic Matching Reinforcement Learning Model CVPR 2019 Large-Scale Interactive Recommendation with Tree-Structured Policy Gradient AAAI 2019 Large Scale Markov Decision Processes with Changing Rewards NeurIPS 2019 Large-Scale Study of Curiosity-Driven Learning ICLR 2019 Learning Action Representations for Reinforcement Learning ICML 2019 Learning Belief Representations for Imitation Learning in POMDPs UAI 2019 Learning Channel-Wise Interactions for Binary Convolutional Neural Networks CVPR 2019 Learning Compact Models for Planning with Exogenous Processes CoRL 2019 Learning Compositional Neural Programs with Recursive Tree Search and Planning NeurIPS 2019 Learning Dynamic Context Augmentation for Global Entity Linking EMNLP 2019 Learning dynamic polynomial proofs NeurIPS 2019 Learning Factored Markov Decision Processes with Unawareness UAI 2019 Learning from Trajectories via Subgoal Discovery NeurIPS 2019 Learning Interpretable Negation Rules via Weak Supervision at Document Level: A Reinforcement Learning Approach NAACL 2019 Learning Interpretable Relational Structures of Hinge-loss Markov Random Fields IJCAI 2019 Learning Local Search Heuristics for Boolean Satisfiability NeurIPS 2019 Learning Multi-Level Hierarchies with Hindsight ICLR 2019 Learning Personalized Modular Network Guided by Structured Knowledge CVPR 2019 Learning Representations in Model-Free Hierarchical Reinforcement Learning AAAI 2019 Learning Resource Allocation and Pricing for Cloud Profit Maximization AAAI 2019 Learning Self-Imitating Diverse Policies ICLR 2019 Learning the Extraction Order of Multiple Relational Facts in a Sentence with Reinforcement Learning EMNLP 2019 Learning to Adapt in Dynamic, Real-World Environments through Meta-Reinforcement Learning ICLR 2019