sample efficiency

Hierarchical Reinforcement Learning by Discovering Intrinsic Options ICLR 2021 How Are Learned Perception-Based Controllers Impacted by the Limits of Robust Control? L4DC 2021 Hyperparameter Transfer Learning with Adaptive Complexity AISTATS 2021 Improving Sample Efficiency in Model-Free Reinforcement Learning from Images AAAI 2021 Instabilities of Offline RL with Pre-Trained Neural Representation ICML 2021 Interactive Learning from Activity Description ICML 2021 Learning to Execute: Efficient Learning of Universal Plan-Conditioned Policies in Robotics NeurIPS 2021 Learning to Reweight Imaginary Transitions for Model-Based Reinforcement Learning AAAI 2021 Learning to Sample with Local and Global Contexts in Experience Replay Buffer ICLR 2021 `Less Than One'-Shot Learning: Learning N Classes From M < N Samples AAAI 2021 LTL2Action: Generalizing LTL Instructions for Multi-Task RL ICML 2021 MADE: Exploration via Maximizing Deviation from Explored Regions NeurIPS 2021 MapGo: Model-Assisted Policy Optimization for Goal-Oriented Tasks IJCAI 2021 Mastering Atari with Discrete World Models ICLR 2021 Meta-Model-Based Meta-Policy Optimization ACML 2021 Mind Your Outliers! Investigating the Negative Impact of Outliers on Active Learning for Visual Question Answering ACL 2021 Model-based Multi-agent Policy Optimization with Adaptive Opponent-wise Rollouts IJCAI 2021 Model-Based Reinforcement Learning via Imagination with Derived Memory NeurIPS 2021 Modularity in Reinforcement Learning via Algorithmic Independence in Credit Assignment ICML 2021 Muppet: Massive Multi-task Representations with Pre-Finetuning EMNLP 2021 On Effective Scheduling of Model-based Reinforcement Learning NeurIPS 2021 Outside the Echo Chamber: Optimizing the Performative Risk ICML 2021 PC-MLP: Model-based Reinforcement Learning with Policy Cover Guided Exploration ICML 2021 Phasic Policy Gradient ICML 2021 Plan-Based Relaxed Reward Shaping for Goal-Directed Tasks ICLR 2021