Articles with public access mandates - Yingying LiLearn more
Available somewhere: 12
Online optimization with predictions and switching costs: Fast algorithms and the fundamental limit
Y Li, G Qu, N Li
IEEE Transactions on Automatic Control, 2020
Mandates: US National Science Foundation, US Department of Energy, US Department of …
Distributed reinforcement learning for decentralized linear quadratic control: A derivative-free policy optimization approach
Y Li, Y Tang, R Zhang, N Li
IEEE Transactions on Automatic Control 67 (12), 6429-6444, 2021
Mandates: US National Science Foundation, US Department of Defense
Online optimal control with linear dynamics and predictions: Algorithms and regret analysis
Y Li, X Chen, N Li
Advances in Neural Information Processing Systems 32, 2019
Mandates: US National Science Foundation, US Department of Energy, US Department of …
A reliability-aware multi-armed bandit approach to learn and select users in demand response
Y Li, Q Hu, N Li
Automatica 119, 109015, 2020
Mandates: US National Science Foundation, US Department of Energy, US Department of …
Online hyperparameter optimization for class-incremental learning
Y Liu, Y Li, B Schiele, Q Sun
Proceedings of the AAAI Conference on Artificial Intelligence 37 (7), 8906-8913, 2023
Mandates: A*Star, Singapore
Online learning and distributed control for residential demand response
X Chen, Y Li, J Shimada, N Li
IEEE Transactions on Smart Grid 12 (6), 4843-4853, 2021
Mandates: US National Science Foundation
Non-asymptotic system identification for linear systems with nonlinear policies
Y Li, T Zhang, S Das, J Shamma, N Li
IFAC-PapersOnLine 56 (2), 1672-1679, 2023
Mandates: US National Science Foundation, US Department of Defense
Growing optimal scale-free networks via likelihood
M Small, Y Li, T Stemler, K Judd
Physical Review E 91 (4), 042801, 2015
Mandates: Australian Research Council
Leveraging predictions in smoothed online convex optimization via gradient-based algorithms
Y Li, N Li
Advances in Neural Information Processing Systems 33, 14520-14531, 2020
Mandates: US National Science Foundation, US Department of Defense
Online learning for markov decision processes in nonstationary environments: A dynamic regret analysis
Y Li, N Li
2019 American Control Conference (ACC), 1232-1237, 2019
Mandates: US National Science Foundation, US Department of Energy, US Department of …
Online markov decision processes with time-varying transition probabilities and rewards
Y Li, A Zhong, G Qu, N Li
ICML workshop on Real-world Sequential Decision Making 3, 2019
Mandates: US National Science Foundation, US Department of Energy, US Department of …
Mechanism design for reliability in demand response with uncertainty
Y Li, N Li
2017 American control conference (ACC), 3400-3405, 2017
Mandates: US National Science Foundation
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