Reinforcement Learning

Learning how to Active Learn: A Deep Reinforcement Learning Approach EMNLP 2017 Mapping Instructions and Visual Observations to Actions with Reinforcement Learning EMNLP 2017 Multi-Modal Imitation Learning from Unstructured Demonstrations using Generative Adversarial Nets NeurIPS 2017 Natural Value Approximators: Learning when to Trust Past Estimates NeurIPS 2017 Optimistic posterior sampling for reinforcement learning: worst-case regret bounds NeurIPS 2017 ParlAI: A Dialog Research Software Platform EMNLP 2017 PoseAgent: Budget-Constrained 6D Object Pose Estimation via Reinforcement Learning CVPR 2017 Reinforced Video Captioning with Entailment Rewards EMNLP 2017 Reinforcement Learning under Model Mismatch NeurIPS 2017 Repeated Inverse Reinforcement Learning NeurIPS 2017 Robust and Efficient Transfer Learning with Hidden Parameter Markov Decision Processes NeurIPS 2017 Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation NeurIPS 2017 Successor Features for Transfer in Reinforcement Learning NeurIPS 2017 Towards End-to-End Reinforcement Learning of Dialogue Agents for Information Access ACL 2017 Adaptive Skills Adaptive Partitions (ASAP) NeurIPS 2016 Cooperative Inverse Reinforcement Learning NeurIPS 2016 Generating Long-term Trajectories Using Deep Hierarchical Networks NeurIPS 2016 Learning under uncertainty: a comparison between R-W and Bayesian approach NeurIPS 2016 Learning values across many orders of magnitude NeurIPS 2016 PAC Reinforcement Learning with Rich Observations NeurIPS 2016 Reinforcement Learning for Visual Object Detection CVPR 2016 Data Generation as Sequential Decision Making NeurIPS 2015 Fighting Bandits with a New Kind of Smoothness NeurIPS 2015 Gradient Estimation Using Stochastic Computation Graphs NeurIPS 2015 Policy Evaluation Using the Ω-Return NeurIPS 2015