sample efficiency

Towards Sample Efficient Agents through Algorithmic Alignment (Student Abstract) AAAI 2021 Uncertainty-Aware Policy Optimization: A Robust, Adaptive Trust Region Approach AAAI 2021 Variational Model-based Policy Optimization IJCAI 2021 Visual Adversarial Imitation Learning using Variational Models NeurIPS 2021 Widening the Pipeline in Human-Guided Reinforcement Learning with Explanation and Context-Aware Data Augmentation NeurIPS 2021 Actor-Double-Critic: Incorporating Model-Based Critic for Task-Oriented Dialogue Systems EMNLP 2020 Adaptive Smoothing for Path Integral Control JMLR 2020 AMRL: Aggregated Memory For Reinforcement Learning ICLR 2020 An Interpretable and Sample Efficient Deep Kernel for Gaussian Process UAI 2020 A Nonparametric Off-Policy Policy Gradient AISTATS 2020 Attention-Privileged Reinforcement Learning CoRL 2020 Augmenting GAIL with BC for sample efficient imitation learning CoRL 2020 Automatic Curriculum Learning For Deep RL: A Short Survey IJCAI 2020 Auxiliary Tasks Speed Up Learning Point Goal Navigation CoRL 2020 Bayesian Multi-type Mean Field Multi-agent Imitation Learning NeurIPS 2020 Bidirectional Model-based Policy Optimization ICML 2020 BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization NeurIPS 2020 Bridging Imagination and Reality for Model-Based Deep Reinforcement Learning NeurIPS 2020 Can Increasing Input Dimensionality Improve Deep Reinforcement Learning? ICML 2020 Combating False Negatives in Adversarial Imitation Learning (Student Abstract) AAAI 2020 Count-Based Exploration with the Successor Representation AAAI 2020 Counterfactual Data Augmentation using Locally Factored Dynamics NeurIPS 2020 Deep Coordination Graphs ICML 2020 Deep Model-Based Reinforcement Learning via Estimated Uncertainty and Conservative Policy Optimization AAAI 2020 Deep Reinforcement Learning with Robust and Smooth Policy ICML 2020