Reinforcement Learning

Unsupervised Conversation Disentanglement through Co-Training EMNLP 2021 Unsupervised Domain Adaptation with Dynamics-Aware Rewards in Reinforcement Learning NeurIPS 2021 Unsupervised Learning for Robust Fitting: A Reinforcement Learning Approach CVPR 2021 Unsupervised Learning of Visual 3D Keypoints for Control ICML 2021 Unsupervised program synthesis for images by sampling without replacement UAI 2021 Unsupervised Visual Attention and Invariance for Reinforcement Learning CVPR 2021 Urban Driver: Learning to Drive from Real-world Demonstrations Using Policy Gradients CoRL 2021 Using Question Answering Rewards to Improve Abstractive Summarization EMNLP 2021 Value-Decomposition Multi-Agent Actor-Critics AAAI 2021 Value Iteration in Continuous Actions, States and Time ICML 2021 Variable Frame Rate Acoustic Models Using Minimum Error Reinforcement Learning Interspeech 2021 Variance-Aware Off-Policy Evaluation with Linear Function Approximation NeurIPS 2021 Variance Penalized On-Policy and Off-Policy Actor-Critic AAAI 2021 Variational Automatic Curriculum Learning for Sparse-Reward Cooperative Multi-Agent Problems NeurIPS 2021 Variational Bayesian Reinforcement Learning with Regret Bounds NeurIPS 2021 Variational Empowerment as Representation Learning for Goal-Conditioned Reinforcement Learning ICML 2021 Variational Intrinsic Control Revisited ICLR 2021 Variational Model-based Policy Optimization IJCAI 2021 VariBAD: Variational Bayes-Adaptive Deep RL via Meta-Learning JMLR 2021 VAST: Value Function Factorization with Variable Agent Sub-Teams NeurIPS 2021 Vector Quantized Models for Planning ICML 2021 Verifying Reinforcement Learning up to Infinity IJCAI 2021 Visual Adversarial Imitation Learning using Variational Models NeurIPS 2021 Visual Comfort Aware-Reinforcement Learning for Depth Adjustment of Stereoscopic 3D Images AAAI 2021 Visual-Locomotion: Learning to Walk on Complex Terrains with Vision CoRL 2021