Ding, Yuhao

12 publications

JAIR 2025 Policy-Based Primal-Dual Methods for Concave CMDP with Variance Reduction Donghao Ying, Mengzi Amy Guo, Hyunin Lee, Yuhao Ding, Javad Lavaei, Zuo-Jun Max Shen

AAAI 2024 Balance Reward and Safety Optimization for Safe Reinforcement Learning: A Perspective of Gradient Manipulation Shangding Gu, Bilgehan Sel, Yuhao Ding, Lu Wang, Qingwei Lin, Ming Jin, Alois Knoll

NeurIPS 2024 Enhancing Efficiency of Safe Reinforcement Learning via Sample Manipulation Shangding Gu, Laixi Shi, Yuhao Ding, Alois Knoll, Costas Spanos, Adam Wierman, Ming Jin

ICLR 2023 A CMDP-Within-Online Framework for Meta-Safe Reinforcement Learning Vanshaj Khattar, Yuhao Ding, Bilgehan Sel, Javad Lavaei, Ming Jin

L4DC 2023 Learning-to-Learn to Guide Random Search: Derivative-Free Meta Blackbox Optimization on Manifold Bilgehan Sel, Ahmad Tawaha, Yuhao Ding, Ruoxi Jia, Bo Ji, Javad Lavaei, Ming Jin

AAAI 2023 Non-Stationary Risk-Sensitive Reinforcement Learning: Near-Optimal Dynamic Regret, Adaptive Detection, and Separation Design Yuhao Ding, Ming Jin, Javad Lavaei

AAAI 2023 Policy-Based Primal-Dual Methods for Convex Constrained Markov Decision Processes Donghao Ying, Mengzi Amy Guo, Yuhao Ding, Javad Lavaei, Zuo-Jun Max Shen

AAAI 2023 Provably Efficient Primal-Dual Reinforcement Learning for CMDPs with Non-Stationary Objectives and Constraints Yuhao Ding, Javad Lavaei

NeurIPS 2023 Scalable Primal-Dual Actor-Critic Method for Safe Multi-Agent RL with General Utilities Donghao Ying, Yunkai Zhang, Yuhao Ding, Alec Koppel, Javad Lavaei

NeurIPS 2023 Tempo Adaptation in Non-Stationary Reinforcement Learning Hyunin Lee, Yuhao Ding, Jongmin Lee, Ming Jin, Javad Lavaei, Somayeh Sojoudi

AISTATS 2022 A Dual Approach to Constrained Markov Decision Processes with Entropy Regularization Donghao Ying, Yuhao Ding, Javad Lavaei

AISTATS 2022 On the Global Optimum Convergence of Momentum-Based Policy Gradient Yuhao Ding, Junzi Zhang, Javad Lavaei