Beyond Online Balanced Descent: An Optimal Algorithm for Smoothed Online Optimization. - Gautam Goel; Yiheng Lin 001; Haoyuan Sun; Adam Wierman (NeurIPS, 2019)

Scalable Multi-Agent Reinforcement Learning for Networked Systems with Average Reward. - Guannan Qu; Yiheng Lin 001; Adam Wierman; Na Li 002 (NeurIPS, 2020)

Online Optimization with Memory and Competitive Control. - Guanya Shi; Yiheng Lin 001; Soon-Jo Chung; Yisong Yue; Adam Wierman (NeurIPS, 2020)

Beyond No-Regret: Competitive Control via Online Optimization with Memory. - Guanya Shi; Yiheng Lin 001; Soon-Jo Chung; Yisong Yue; Adam Wierman (CoRR, 2020)

Distributed Reinforcement Learning in Multi-Agent Networked Systems. - Yiheng Lin 001; Guannan Qu; Longbo Huang; Adam Wierman (CoRR, 2020)

Online Optimization with Predictions and Non-convex Losses. - Yiheng Lin 001; Gautam Goel; Adam Wierman (Proc. ACM Meas. Anal. Comput. Syst., 2020)

Online Optimization with Predictions and Non-convex Losses. - Yiheng Lin 001 (CISS, 2021)

Perturbation-based Regret Analysis of Predictive Control in Linear Time Varying Systems. - Yiheng Lin 001; Yang Hu; Guanya Shi; Haoyuan Sun; Guannan Qu; Adam Wierman (NeurIPS, 2021)

Multi-Agent Reinforcement Learning in Stochastic Networked Systems. - Yiheng Lin 001; Guannan Qu; Longbo Huang; Adam Wierman (NeurIPS, 2021)

Decentralized Online Convex Optimization in Networked Systems. - Yiheng Lin 001; Judy Gan; Guannan Qu; Yash Kanoria; Adam Wierman (ICML, 2022)

Bounded-Regret MPC via Perturbation Analysis: Prediction Error, Constraints, and Nonlinearity. - Yiheng Lin 001; Yang Hu; Guannan Qu; Tongxin Li; Adam Wierman (NeurIPS, 2022)

Equipping Black-Box Policies with Model-Based Advice for Stable Nonlinear Control. - Tongxin Li; Ruixiao Yang; Guannan Qu; Yiheng Lin 001; Steven H. Low; Adam Wierman (CoRR, 2022)

Online Optimization with Feedback Delay and Nonlinear Switching Cost. - Weici Pan; Guanya Shi; Yiheng Lin 001; Adam Wierman (Proc. ACM Meas. Anal. Comput. Syst., 2022)

Online switching control with stability and regret guarantees. - Yingying Li; James A. Preiss; Na Li 002; Yiheng Lin 001; Adam Wierman; Jeff S. Shamma (L4DC, 2023)

Beyond Black-Box Advice: Learning-Augmented Algorithms for MDPs with Q-Value Predictions. - Tongxin Li; Yiheng Lin 001; Shaolei Ren; Adam Wierman (NeurIPS, 2023)

Online Adaptive Policy Selection in Time-Varying Systems: No-Regret via Contractive Perturbations. - Yiheng Lin 001; James A. Preiss; Emile Anand; Yingying Li; Yisong Yue; Adam Wierman (NeurIPS, 2023)

Convergence rates for localized actor-critic in networked Markov potential games. - Zhaoyi Zhou; Zaiwei Chen; Yiheng Lin 001; Adam Wierman (UAI, 2023)

Global Convergence of Localized Policy Iteration in Networked Multi-Agent Reinforcement Learning. - Yizhou Zhang; Guannan Qu; Pan Xu 002; Yiheng Lin 001; Zaiwei Chen; Adam Wierman (Proc. ACM Meas. Anal. Comput. Syst., 2023)

Near-Optimal Distributed Linear-Quadratic Regulator for Networked Systems. - Sungho Shin; Yiheng Lin 001; Guannan Qu; Adam Wierman; Mihai Anitescu (SIAM J. Control. Optim., 2023)

Characterizing Controllability and Observability for Systems with Locality, Communication, and Actuation Constraints. - Lauren E. Conger; Yiheng Lin 001; Adam Wierman; Eric Mazumdar (CDC, 2024)

Online Policy Optimization in Unknown Nonlinear Systems. - Yiheng Lin 001; James A. Preiss; Fengze Xie; Emile Anand; Soon-Jo Chung; Yisong Yue; Adam Wierman (COLT, 2024)

SODA: An Adaptive Bitrate Controller for Consistent High-Quality Video Streaming. - Tianyu Chen; Yiheng Lin 001; Nicolas Christianson; Zahaib Akhtar; Sharath Dharmaji; Mohammad Hajiesmaili; Adam Wierman; Ramesh K. Sitaraman (SIGCOMM, 2024)

Approximate Global Convergence of Independent Learning in Multi-Agent Systems. - Ruiyang Jin; Zaiwei Chen; Yiheng Lin 001; Jie Song 002; Adam Wierman (AISTATS, 2025)

Fast Non-Episodic Adaptive Tuning of Robot Controllers with Online Policy Optimization. - James A. Preiss; Fengze Xie; Yiheng Lin 001; Adam Wierman; Yisong Yue (CoRR, 2025)