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Deep RL

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Balance Reward and Safety Optimization for Safe Reinforcement Learning: A Perspective of Gradient Manipulation AAAI 2024
Rethinking Discount Regularization: New Interpretations, Unintended Consequences, and Solutions for Regularization in Reinforcement Learning JMLR 2024
Sample-efficient Adversarial Imitation Learning JMLR 2024
Efficient Reinforcement Learning for Routing Jobs in Heterogeneous Queueing Systems AISTATS 2024
Robust Black-Box Optimization for Stochastic Search and Episodic Reinforcement Learning JMLR 2024
Pearl: A Production-Ready Reinforcement Learning Agent JMLR 2024
Exploration via linearly perturbed loss minimisation AISTATS 2024
Distributionally Robust Off-Dynamics Reinforcement Learning: Provable Efficiency with Linear Function Approximation AISTATS 2024
Sampling-based Safe Reinforcement Learning for Nonlinear Dynamical Systems AISTATS 2024
Watch Every Step! LLM Agent Learning via Iterative Step-level Process Refinement EMNLP 2024
Horizon-Free and Instance-Dependent Regret Bounds for Reinforcement Learning with General Function Approximation AISTATS 2024
Finding a Needle in the Adversarial Haystack: A Targeted Paraphrasing Approach For Uncovering Edge Cases with Minimal Distribution Distortion EACL 2024
Privacy-Constrained Policies via Mutual Information Regularized Policy Gradients AISTATS 2024
Learning Dynamic Mechanisms in Unknown Environments: A Reinforcement Learning Approach JMLR 2024
VLMPC: Vision-Language Model Predictive Control for Robotic Manipulation RSS 2024
Safeguarded Progress in Reinforcement Learning: Safe Bayesian Exploration for Control Policy Synthesis AAAI 2024
On learning history-based policies for controlling Markov decision processes AISTATS 2024
Model-based Policy Optimization under Approximate Bayesian Inference AISTATS 2024
Policy Evaluation for Reinforcement Learning from Human Feedback: A Sample Complexity Analysis AISTATS 2024
MIM-Reasoner: Learning with Theoretical Guarantees for Multiplex Influence Maximization AISTATS 2024
Distributionally Robust Model-based Reinforcement Learning with Large State Spaces AISTATS 2024
Handling Long and Richly Constrained Tasks through Constrained Hierarchical Reinforcement Learning AAAI 2024
A Cubic-regularized Policy Newton Algorithm for Reinforcement Learning AISTATS 2024
Fast Policy Extragradient Methods for Competitive Games with Entropy Regularization JMLR 2024
Bit_numeval at SemEval-2024 Task 7: Enhance Numerical Sensitivity and Reasoning Completeness for Quantitative Understanding SEMEVAL 2024