Policy Learning

Spotlight News Driven Quantitative Trading Based on Trajectory Optimization IJCAI 2023 State-Conditioned Adversarial Subgoal Generation AAAI 2023 State Regularized Policy Optimization on Data with Dynamics Shift NeurIPS 2023 STEER: Unified Style Transfer with Expert Reinforcement EMNLP 2023 Stochastic Policy Gradient Methods: Improved Sample Complexity for Fisher-non-degenerate Policies ICML 2023 Struct-XLM: A Structure Discovery Multilingual Language Model for Enhancing Cross-lingual Transfer through Reinforcement Learning EMNLP 2023 Symmetric (Optimistic) Natural Policy Gradient for Multi-Agent Learning with Parameter Convergence AISTATS 2023 Synthesizing Diverse Human Motions in 3D Indoor Scenes ICCV 2023 Taming Continuous Posteriors for Latent Variational Dialogue Policies AAAI 2023 Target-to-Source Augmentation for Aspect Sentiment Triplet Extraction EMNLP 2023 Task-Oriented Koopman-Based Control with Contrastive Encoder CoRL 2023 Tempo Adaptation in Non-stationary Reinforcement Learning NeurIPS 2023 TGRL: An Algorithm for Teacher Guided Reinforcement Learning ICML 2023 The Power of Learned Locally Linear Models for Nonlinear Policy Optimization ICML 2023 The Regret of Exploration and the Control of Bad Episodes in Reinforcement Learning ICML 2023 The Sufficiency of Off-Policyness and Soft Clipping: PPO Is Still Insufficient according to an Off-Policy Measure AAAI 2023 The Unintended Consequences of Discount Regularization: Improving Regularization in Certainty Equivalence Reinforcement Learning ICML 2023 Thought Cloning: Learning to Think while Acting by Imitating Human Thinking NeurIPS 2023 Tight Performance Guarantees of Imitator Policies with Continuous Actions AAAI 2023 Timing is Everything: Learning to Act Selectively with Costly Actions and Budgetary Constraints ICLR 2023 Towards Hierarchical Policy Learning for Conversational Recommendation with Hypergraph-based Reinforcement Learning IJCAI 2023 Towards Learning to Imitate from a Single Video Demonstration JMLR 2023 Towards Theoretical Understanding of Inverse Reinforcement Learning ICML 2023 Train Hard, Fight Easy: Robust Meta Reinforcement Learning NeurIPS 2023 Train Once, Get a Family: State-Adaptive Balances for Offline-to-Online Reinforcement Learning NeurIPS 2023