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

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)

Scalable Multi-Agent Reinforcement Learning with General Utilities. - Donghao Ying; Yuhao Ding; Alec Koppel; Javad Lavaei (ACC, 2023)

No-Regret Learning in Dynamic Competition with Reference Effects Under Logit Demand. - Mengzi Amy Guo; Donghao Ying; Javad Lavaei; Zuo-Jun Max Shen (NeurIPS, 2023)

Scalable Primal-Dual Actor-Critic Method for Safe Multi-Agent RL with General Utilities. - Donghao Ying; Yunkai Zhang 002; Yuhao Ding; Alec Koppel; Javad Lavaei (NeurIPS, 2023)

Bagging Improves Generalization Exponentially. - Huajie Qian; Donghao Ying; Henry Lam; Wotao Yin (CoRR, 2024)

A Hitting Time Analysis for Stochastic Time-Varying Functions With Applications to Adversarial Attacks on Computation of Markov Decision Processes. - Ali Yekkehkhany; Han Feng; Donghao Ying; Javad Lavaei (IEEE Trans. Autom. Control., 2024)

Towards VM Rescheduling Optimization Through Deep Reinforcement Learning. - Xianzhong Ding; Yunkai Zhang 002; Binbin Chen 005; Donghao Ying; Tieying Zhang; Jianjun Chen 001; Lei Zhang; Alberto Cerpa; Wan Du (EuroSys, 2025)

Reward-Safety Balance in Offline Safe RL via Diffusion Regularization. - Junyu Guo; Zhi Zheng; Donghao Ying; Ming Jin 002; Shangding Gu; Costas J. Spanos; Javad Lavaei (CoRR, 2025)

Few-Shot Test-Time Optimization Without Retraining for Semiconductor Recipe Generation and Beyond. - Shangding Gu; Donghao Ying; Ming Jin 002; Yu Joe Lu; Jun Wang 012; Javad Lavaei; Costas J. Spanos (CoRR, 2025)