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Yiheng Lin
Yiheng Lin
Adresse e-mail validée de caltech.edu - Page d'accueil
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Année
Beyond Online Balanced Descent: An Optimal Algorithm for Smoothed Online Optimization
G Goel, Y Lin, H Sun, A Wierman
Advances in Neural Information Processing Systems 32 (2019), 1875-1885, 2019
652019
Scalable Multi-Agent Reinforcement Learning for Networked Systems with Average Reward
G Qu, Y Lin, A Wierman, N Li
Advances in Neural Information Processing Systems 33 (2020), 2074-2086, 2020
582020
Online Optimization with Memory and Competitive Control
G Shi, Y Lin, SJ Chung, Y Yue, A Wierman
Advances in Neural Information Processing Systems 33 (2020), 20636-20647, 2020
49*2020
Online optimization with predictions and non-convex losses
Y Lin, G Goel, A Wierman
Proceedings of the ACM on Measurement and Analysis of Computing Systems 4 (1 …, 2020
412020
Multi-agent reinforcement learning in stochastic networked systems
Y Lin, G Qu, L Huang, A Wierman
Advances in neural information processing systems 34, 7825-7837, 2021
37*2021
Perturbation-based regret analysis of predictive control in linear time varying systems
Y Lin, Y Hu, G Shi, H Sun, G Qu, A Wierman
Advances in Neural Information Processing Systems 34, 5174-5185, 2021
312021
Near-optimal distributed linear-quadratic regulator for networked systems
S Shin, Y Lin, G Qu, A Wierman, M Anitescu
SIAM Journal on Control and Optimization 61 (3), 1113-1135, 2023
152023
Distributed reinforcement learning in multi-agent networked systems
Y Lin, G Qu, L Huang, A Wierman
arXiv preprint arXiv:2006.06555, 2020
152020
Global convergence of localized policy iteration in networked multi-agent reinforcement learning
Y Zhang, G Qu, P Xu, Y Lin, Z Chen, A Wierman
Proceedings of the ACM on Measurement and Analysis of Computing Systems 7 (1 …, 2023
142023
Online optimization with feedback delay and nonlinear switching cost
W Pan, G Shi, Y Lin, A Wierman
Proceedings of the ACM on Measurement and Analysis of Computing Systems 6 (1 …, 2022
92022
Online adaptive controller selection in time-varying systems: No-regret via contractive perturbations
Y Lin, J Preiss, E Anand, Y Li, Y Yue, A Wierman
arXiv preprint arXiv:2210.12320, 2022
72022
Online switching control with stability and regret guarantees
Y Li, JA Preiss, N Li, Y Lin, A Wierman, JS Shamma
Learning for Dynamics and Control Conference, 1138-1151, 2023
62023
Bounded-regret mpc via perturbation analysis: Prediction error, constraints, and nonlinearity
Y Lin, Y Hu, G Qu, T Li, A Wierman
Advances in Neural Information Processing Systems 35, 36174-36187, 2022
62022
Convergence rates for localized actor-critic in networked markov potential games
Z Zhou, Z Chen, Y Lin, A Wierman
Uncertainty in Artificial Intelligence, 2563-2573, 2023
52023
Certifying black-box policies with stability for nonlinear control
T Li, R Yang, G Qu, Y Lin, A Wierman, SH Low
IEEE Open Journal of Control Systems 2, 49-62, 2023
42023
Decentralized online convex optimization in networked systems
Y Lin, J Gan, G Qu, Y Kanoria, A Wierman
International Conference on Machine Learning, 13356-13393, 2022
42022
Equipping black-box policies with model-based advice for stable nonlinear control
T Li, R Yang, G Qu, Y Lin, S Low, A Wierman
arXiv preprint arXiv:2206.01341, 2022
42022
Online adaptive policy selection in time-varying systems: No-regret via contractive perturbations
Y Lin, JA Preiss, E Anand, Y Li, Y Yue, A Wierman
Advances in Neural Information Processing Systems 36, 2024
32024
Beyond Black-Box Advice: Learning-Augmented Algorithms for MDPs with Q-Value Predictions
T Li, Y Lin, S Ren, A Wierman
Advances in Neural Information Processing Systems 36, 2024
22024
Learning-augmented Control via Online Adaptive Policy Selection: No Regret via Contractive Perturbations
Y Lin, JA Preiss, ET Anand, Y Li, Y Yue, A Wierman
ACM SIGMETRICS, Workshop on Learning-augmented Algorithms: Theory and …, 2023
2023
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