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Lintao Ye
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Cited by
Year
On the Complexity and Approximability of Optimal Sensor Selection and Attack for Kalman Filtering
L Ye, N Woodford, S Roy, S Sundaram
IEEE Transactions on Automatic Control 66 (5), 2146-2161, 2020
322020
On the complexity and approximability of optimal sensor selection for Kalman filtering
L Ye, S Roy, S Sundaram
2018 Annual American Control Conference (ACC), 5049-5054, 2018
252018
Identifying the dynamics of a system by leveraging data from similar systems
L Xin, L Ye, G Chiu, S Sundaram
2022 American Control Conference (ACC), 818-824, 2022
212022
Resilient sensor placement for Kalman filtering in networked systems: Complexity and algorithms
L Ye, S Roy, S Sundaram
IEEE Transactions on Control of Network Systems 7 (4), 1870-1881, 2020
172020
On the sample complexity of decentralized linear quadratic regulator with partially nested information structure
L Ye, H Zhu, V Gupta
IEEE Transactions on Automatic Control 68 (8), 4841 - 4856, 2022
122022
Learning dynamical systems by leveraging data from similar systems
L Xin, L Ye, G Chiu, S Sundaram
arXiv preprint arXiv:2302.04344, 2023
82023
Optimal sensor placement for Kalman filtering in stochastically forced consensus networks
L Ye, S Roy, S Sundaram
2018 IEEE Conference on Decision and Control (CDC), 6686-6691, 2018
82018
Distributed maximization of submodular and approximately submodular functions
L Ye, S Sundaram
2020 59th IEEE Conference on Decision and Control (CDC), 2979-2984, 2020
72020
Sensor selection for hypothesis testing: Complexity and greedy algorithms
L Ye, S Sundaram
2019 IEEE 58th Conference on Decision and Control (CDC), 7844-7849, 2019
72019
Client scheduling for federated learning over wireless networks: A submodular optimization approach
L Ye, V Gupta
2021 60th IEEE Conference on Decision and Control (CDC), 63-68, 2021
52021
Model-free learning for risk-constrained linear quadratic regulator with structured feedback in networked systems
K Kwon, L Ye, V Gupta, H Zhu
2022 IEEE 61st Conference on Decision and Control (CDC), 7260-7265, 2022
42022
Online actuator selection and controller design for linear quadratic regulation with unknown system model
L Ye, M Chi, ZW Liu, V Gupta
arXiv preprint arXiv:2201.10197, 2022
4*2022
Near-optimal data source selection for Bayesian learning
L Ye, A Mitra, S Sundaram
Learning for Dynamics and Control, 854-865, 2021
42021
Dissipativity-based Voltage Control in Distribution Grids
KC Kosaraju, L Ye, V Gupta, R Trevizan, B Chalamala, RH Byrne
2022 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference, 2022
22022
Parameter estimation in epidemic spread networks using limited measurements
L Ye, PE Paré, S Sundaram
SIAM Journal on Control and Optimization 60 (2), S49-S74, 2021
22021
Towards Model-Free LQR Control over Rate-Limited Channels
A Mitra, L Ye, V Gupta
arXiv preprint arXiv:2401.01258, 2024
12024
Learning Decentralized Linear Quadratic Regulator with Regret
L Ye, M Chi, R Liao, V Gupta
arXiv preprint arXiv:2210.08886, 2022
1*2022
Resilient Multi-Agent Reinforcement Learning With Function Approximation
L Ye, M Figura, Y Lin, M Pal, P Das, J Liu, V Gupta
IEEE Transactions on Automatic Control, 2024
2024
Decentralized Reactive Power Control in Distribution Grids With Unknown Reactance Matrix
L Ye, KC Kosaraju, V Gupta, RD Trevizan, RH Byrne, BR Chalamala
IEEE Open Access Journal of Power and Energy, 2024
2024
Online Mixed Discrete and Continuous Optimization: Algorithms, Regret Analysis and Applications
L Ye, M Chi, ZW Liu, X Wang, V Gupta
arXiv preprint arXiv:2309.07630, 2023
2023
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