Reinforcement Learning

Exploration in Reinforcement Learning with Deep Covering Options ICLR 2020 Exploratory Combinatorial Optimization with Reinforcement Learning AAAI 2020 Exploratory Grasping: Asymptotically Optimal Algorithms for Grasping Challenging Polyhedral Objects CoRL 2020 Exploratory Not Explanatory: Counterfactual Analysis of Saliency Maps for Deep Reinforcement Learning ICLR 2020 Explore, Discover and Learn: Unsupervised Discovery of State-Covering Skills ICML 2020 Exploring Data Aggregation in Policy Learning for Vision-Based Urban Autonomous Driving CVPR 2020 Exploring Parameter Space with Structured Noise for Meta-Reinforcement Learning IJCAI 2020 Exploring Question-Specific Rewards for Generating Deep Questions COLING 2020 Fast Adaptation to New Environments via Policy-Dynamics Value Functions ICML 2020 Fast computation of Nash Equilibria in Imperfect Information Games ICML 2020 Faster saddle-point optimization for solving large-scale Markov decision processes L4DC 2020 Fast Task Inference with Variational Intrinsic Successor Features ICLR 2020 Fast Template Matching and Update for Video Object Tracking and Segmentation CVPR 2020 Few-Shot Complex Knowledge Base Question Answering via Meta Reinforcement Learning EMNLP 2020 Few-Shot Multi-Hop Relation Reasoning over Knowledge Bases EMNLP 2020 Few-shot Object Grounding and Mapping for Natural Language Robot Instruction Following CoRL 2020 Feynman-Kac Neural Network Architectures for Stochastic Control Using Second-Order FBSDE Theory L4DC 2020 f-GAIL: Learning f-Divergence for Generative Adversarial Imitation Learning NeurIPS 2020 Fiduciary Bandits ICML 2020 Finite-Memory Near-Optimal Learning for Markov Decision Processes with Long-Run Average Reward UAI 2020 Finite-Sample Analysis of Contractive Stochastic Approximation Using Smooth Convex Envelopes NeurIPS 2020 Finite-sample Analysis of Greedy-GQ with Linear Function Approximation under Markovian Noise UAI 2020 Finite-Time Analysis of Decentralized Temporal-Difference Learning with Linear Function Approximation AISTATS 2020 Finite Time Analysis of Linear Two-timescale Stochastic Approximation with Markovian Noise COLT 2020 Finite-Time Error Bounds for Biased Stochastic Approximation with Applications to Q-Learning AISTATS 2020