| 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 | 24 | 2020 |
| 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 | 23 | 2018 |
| 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 | 16 | 2022 |
| 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 | 15 | 2020 |
| 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, 2022 | 9 | 2022 |
| 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 | 8 | 2018 |
| Distributed maximization of submodular and approximately submodular functions L Ye, S Sundaram 2020 59th IEEE Conference on Decision and Control (CDC), 2979-2984, 2020 | 7 | 2020 |
| 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 | 7 | 2019 |
| Learning Dynamical Systems by Leveraging Data from Similar Systems L Xin, L Ye, G Chiu, S Sundaram arXiv preprint arXiv:2302.04344, 2023 | 6 | 2023 |
| 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 | 3 | 2021 |
| Near-optimal data source selection for bayesian learning L Ye, A Mitra, S Sundaram Learning for Dynamics and Control, 854-865, 2021 | 3 | 2021 |
| 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 | 2 | 2021 |
| 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 | 1 | 2022 |
| Regret Bounds for Learning Decentralized Linear Quadratic Regulator with Partially Nested Information Structure L Ye, M Chi, V Gupta arXiv preprint arXiv:2210.08886, 2022 | 1 | 2022 |
| 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 | 1 | 2022 |
| 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 | 1* | 2022 |
| 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 |
| Maximization of nonsubmodular functions under multiple constraints with applications L Ye, ZW Liu, M Chi, V Gupta Automatica 155, 111126, 2023 | | 2023 |
| Algorithmic and Graph-Theoretic Approaches for Optimal Sensor Selection in Large-Scale Systems L Ye Purdue University Graduate School, 2020 | | 2020 |
Shreyas SundaramMarie Gordon Professor of Electrical and Computer Engineering, Purdue UniversityVerified email at purdue.edu
