अनुसरण करें
Lintao Ye
टाइटल
इन्होंने कहा
इन्होंने कहा
वर्ष
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
352020
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
292022
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
272018
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
182020
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
152022
Learning dynamical systems by leveraging data from similar systems
L Xin, L Ye, G Chiu, S Sundaram
IEEE Transactions on Automatic Control, 2025
102025
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
92021
Distributed maximization of submodular and approximately submodular functions
L Ye, S Sundaram
2020 59th IEEE Conference on Decision and Control (CDC), 2979-2984, 2020
92020
Online actuator selection and controller design for linear quadratic regulation with unknown system model
L Ye, M Chi, ZW Liu, V Gupta
IEEE Transactions on Automatic Control 70 (1), 18-33, 2024
8*2024
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
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
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
62022
Near-optimal data source selection for Bayesian learning
L Ye, A Mitra, S Sundaram
Learning for Dynamics and Control, 854-865, 2021
52021
Learning Decentralized Linear Quadratic Regulators with Regret
L Ye, M Chi, R Liao, V Gupta
SIAM Journal on Control and Optimization 62 (6), 3341-3368, 2024
3*2024
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 69 (12), 8497 - 8512, 2024
32024
Towards Model-Free LQR Control over Rate-Limited Channels
A Mitra, L Ye, V Gupta
6th Annual Learning for Dynamics & Control Conference, 1253–1265, 2024
22024
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
Submodular maximization approaches for equitable client selection in federated learning
ACC Jiménez, EC Kaya, L Ye, A Hashemi
arXiv preprint arXiv:2408.13683, 2024
12024
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
12024
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