Policy Learning

Kernel-Based Reinforcement Learning: A Finite-Time Analysis ICML 2021 Known unknowns: Learning novel concepts using reasoning-by-elimination UAI 2021 Langevin Dynamics for Adaptive Inverse Reinforcement Learning of Stochastic Gradient Algorithms JMLR 2021 Language Representations for Generalization in Reinforcement Learning ACML 2021 Last-iterate Convergence of Decentralized Optimistic Gradient Descent/Ascent in Infinite-horizon Competitive Markov Games COLT 2021 Latent Skill Planning for Exploration and Transfer ICLR 2021 Learning and Analyzing Generation Order for Undirected Sequence Models EMNLP 2021 Learning Barrier Certificates: Towards Safe Reinforcement Learning with Zero Training-time Violations NeurIPS 2021 Learning Collaborative Policies to Solve NP-hard Routing Problems NeurIPS 2021 Learning Feasibility to Imitate Demonstrators with Different Dynamics CoRL 2021 Learning Policies with Zero or Bounded Constraint Violation for Constrained MDPs NeurIPS 2021 Learning Rewards From Linguistic Feedback AAAI 2021 Learning Task-Distribution Reward Shaping with Meta-Learning AAAI 2021 Learning Task Sampling Policy for Multitask Learning EMNLP 2021 Learning to Iteratively Solve Routing Problems with Dual-Aspect Collaborative Transformer NeurIPS 2021 Learning to Reach Goals via Iterated Supervised Learning ICLR 2021 Learning to Recommend from Sparse Data via Generative User Feedback AAAI 2021 Learning to Reweight Imaginary Transitions for Model-Based Reinforcement Learning AAAI 2021 Learning to Switch Optimizers for Quadratic Programming ACML 2021 Learning to Weight Imperfect Demonstrations ICML 2021 Leveraging Non-uniformity in First-order Non-convex Optimization ICML 2021 Local policy search with Bayesian optimization NeurIPS 2021 Logical Team Q-learning: An approach towards factored policies in cooperative MARL AISTATS 2021 Logistic Q-Learning AISTATS 2021 LTL-Constrained Steady-State Policy Synthesis IJCAI 2021