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 | 68 | 2019 |
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 | 63 | 2020 |
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 | 52* | 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 | 45 | 2020 |
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 | 41* | 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 | 35 | 2021 |
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 | 20 | 2023 |
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 | 16 | 2023 |
Distributed reinforcement learning in multi-agent networked systems Y Lin, G Qu, L Huang, A Wierman arXiv preprint arXiv:2006.06555, 2020 | 15 | 2020 |
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 | 10 | 2023 |
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 | 10 | 2022 |
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 | 9 | 2022 |
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 | 7 | 2023 |
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 | 7 | 2022 |
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 | 6 | 2022 |
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 | 5 | 2024 |
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 | 5 | 2023 |
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 | 4 | 2022 |
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 | 2 | 2024 |
Approximate Global Convergence of Independent Learning in Multi-Agent Systems R Jin, Z Chen, Y Lin, J Song, A Wierman arXiv preprint arXiv:2405.19811, 2024 | | 2024 |