Yiheng Lin

According to our database, Yiheng Lin authored at least 24 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Fast Non-Episodic Adaptive Tuning of Robot Controllers with Online Policy Optimization.

James A. Preiss, Fengze Xie, Yiheng Lin, Adam Wierman, Yisong Yue

CoRR, July, 2025

Approximate Global Convergence of Independent Learning in Multi-Agent Systems.

Ruiyang Jin, Zaiwei Chen, Yiheng Lin, Jie Song, Adam Wierman

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024

SODA: An Adaptive Bitrate Controller for Consistent High-Quality Video Streaming.

Tianyu Chen, Yiheng Lin, Nicolas Christianson, Zahaib Akhtar, Sharath Dharmaji, Mohammad Hajiesmaili, Adam Wierman, Ramesh K. Sitaraman

Proceedings of the ACM SIGCOMM 2024 Conference, 2024

Online Policy Optimization in Unknown Nonlinear Systems.

Yiheng Lin, James A. Preiss, Fengze Xie, Emile Anand, Soon-Jo Chung, Yisong Yue, Adam Wierman

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

Characterizing Controllability and Observability for Systems with Locality, Communication, and Actuation Constraints.

Lauren E. Conger, Yiheng Lin, Adam Wierman, Eric Mazumdar

Proceedings of the 63rd IEEE Conference on Decision and Control, 2024

2023

Near-Optimal Distributed Linear-Quadratic Regulator for Networked Systems.

Sungho Shin, Yiheng Lin, Guannan Qu, Adam Wierman, Mihai Anitescu

SIAM J. Control. Optim., June, 2023

Global Convergence of Localized Policy Iteration in Networked Multi-Agent Reinforcement Learning.

Yizhou Zhang, Guannan Qu, Pan Xu, Yiheng Lin, Zaiwei Chen, Adam Wierman

Proc. ACM Meas. Anal. Comput. Syst., March, 2023

Convergence rates for localized actor-critic in networked Markov potential games.

Zhaoyi Zhou, Zaiwei Chen, Yiheng Lin, Adam Wierman

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Online Adaptive Policy Selection in Time-Varying Systems: No-Regret via Contractive Perturbations.

Yiheng Lin, James A. Preiss, Emile Anand, Yingying Li, Yisong Yue, Adam Wierman

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Beyond Black-Box Advice: Learning-Augmented Algorithms for MDPs with Q-Value Predictions.

Tongxin Li, Yiheng Lin, Shaolei Ren, Adam Wierman

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Online switching control with stability and regret guarantees.

Yingying Li, James A. Preiss, Na Li, Yiheng Lin, Adam Wierman, Jeff S. Shamma

Proceedings of the Learning for Dynamics and Control Conference, 2023

2022

Online Optimization with Feedback Delay and Nonlinear Switching Cost.

Weici Pan, Guanya Shi, Yiheng Lin, Adam Wierman

Proc. ACM Meas. Anal. Comput. Syst., 2022

Equipping Black-Box Policies with Model-Based Advice for Stable Nonlinear Control.

Tongxin Li, Ruixiao Yang, Guannan Qu, Yiheng Lin, Steven H. Low, Adam Wierman

CoRR, 2022

Bounded-Regret MPC via Perturbation Analysis: Prediction Error, Constraints, and Nonlinearity.

Yiheng Lin, Yang Hu, Guannan Qu, Tongxin Li, Adam Wierman

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Decentralized Online Convex Optimization in Networked Systems.

Yiheng Lin, Judy Gan, Guannan Qu, Yash Kanoria, Adam Wierman

Proceedings of the International Conference on Machine Learning, 2022

2021

Multi-Agent Reinforcement Learning in Stochastic Networked Systems.

Yiheng Lin, Guannan Qu, Longbo Huang, Adam Wierman

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Perturbation-based Regret Analysis of Predictive Control in Linear Time Varying Systems.

Yiheng Lin, Yang Hu, Guanya Shi, Haoyuan Sun, Guannan Qu, Adam Wierman

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Online Optimization with Predictions and Non-convex Losses.

Yiheng Lin

Proceedings of the 55th Annual Conference on Information Sciences and Systems, 2021

2020

Online Optimization with Predictions and Non-convex Losses.

Yiheng Lin, Gautam Goel, Adam Wierman

Proc. ACM Meas. Anal. Comput. Syst., 2020

Distributed Reinforcement Learning in Multi-Agent Networked Systems.

Yiheng Lin, Guannan Qu, Longbo Huang, Adam Wierman

CoRR, 2020

Beyond No-Regret: Competitive Control via Online Optimization with Memory.

Guanya Shi, Yiheng Lin, Soon-Jo Chung, Yisong Yue, Adam Wierman

CoRR, 2020

Online Optimization with Memory and Competitive Control.

Guanya Shi, Yiheng Lin, Soon-Jo Chung, Yisong Yue, Adam Wierman

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Scalable Multi-Agent Reinforcement Learning for Networked Systems with Average Reward.

Guannan Qu, Yiheng Lin, Adam Wierman, Na Li

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Beyond Online Balanced Descent: An Optimal Algorithm for Smoothed Online Optimization.

Gautam Goel, Yiheng Lin, Haoyuan Sun, Adam Wierman

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019