Methods

Experimental design for MRI by greedy policy search NeurIPS 2020 Expert-Supervised Reinforcement Learning for Offline Policy Learning and Evaluation NeurIPS 2020 Explainable Agency in Reinforcement Learning Agents AAAI 2020 Explicitly Encouraging Low Fractional Dimensional Trajectories Via Reinforcement Learning CoRL 2020 Explicit Mean-Square Error Bounds for Monte-Carlo and Linear Stochastic Approximation AISTATS 2020 Exploration Analysis in Finite-Horizon Turn-based Stochastic Games UAI 2020 Exploration Based Language Learning for Text-Based Games IJCAI 2020 Exploration in Reinforcement Learning with Deep Covering Options ICLR 2020 Exploratory Combinatorial Optimization with Reinforcement Learning AAAI 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 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