sample efficiency

Deterministic Value-Policy Gradients AAAI 2020 Do We Need to Create Big Datasets to Learn a Task? EMNLP 2020 Efficient Planning under Partial Observability with Unnormalized Q Functions and Spectral Learning AISTATS 2020 Episodic Reinforcement Learning with Associative Memory ICLR 2020 ERLP: Ensembles of Reinforcement Learning Policies (Student Abstract) AAAI 2020 f-IRL: Inverse Reinforcement Learning via State Marginal Matching CoRL 2020 Generalized Representation Learning Methods for Deep Reinforcement Learning IJCAI 2020 Generative Adversarial Imitation Learning from Failed Experiences (Student Abstract) AAAI 2020 High Acceleration Reinforcement Learning for Real-World Juggling with Binary Rewards CoRL 2020 Imitation Learning via Off-Policy Distribution Matching ICLR 2020 IMPACT: Importance Weighted Asynchronous Architectures with Clipped Target Networks ICLR 2020 Implicit Distributional Reinforcement Learning NeurIPS 2020 Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning ICML 2020 Learning Self-Correctable Policies and Value Functions from Demonstrations with Negative Sampling ICLR 2020 Learning to Plan in High Dimensions via Neural Exploration-Exploitation Trees ICLR 2020 Leveraging Procedural Generation to Benchmark Reinforcement Learning ICML 2020 Maximum Entropy Gain Exploration for Long Horizon Multi-goal Reinforcement Learning ICML 2020 Model-Augmented Actor-Critic: Backpropagating through Paths ICLR 2020 On Bonus Based Exploration Methods In The Arcade Learning Environment ICLR 2020 Only Relevant Information Matters: Filtering Out Noisy Samples To Boost RL IJCAI 2020 PixL2R: Guiding Reinforcement Learning Using Natural Language by Mapping Pixels to Rewards CoRL 2020 Predictive Information Accelerates Learning in RL NeurIPS 2020 Provably Efficient Online Hyperparameter Optimization with Population-Based Bandits NeurIPS 2020 RD$^2$: Reward Decomposition with Representation Decomposition NeurIPS 2020 Ready Policy One: World Building Through Active Learning ICML 2020