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2020 – today
- 2025
[j14]Lintao Ye, Ming Chi, Zhi-Wei Liu, Xiaoling Wang, Vijay Gupta:
Online mixed discrete and continuous optimization: Algorithms, regret analysis and applications. Autom. 175: 112189 (2025)- [j13]Lintao Ye
, Ming Chi, Zhi-Wei Liu, Vijay Gupta:
Online Actuator Selection and Controller Design for Linear Quadratic Regulation With an Unknown System Model. IEEE Trans. Autom. Control. 70(1): 18-33 (2025) - [j12]Ze-Qiang Liu, Zhi-Wei Liu, Ding-Xin He, Lintao Ye, Ming Chi:
Dynamic Resilient Consensus of Second-Order Multiagent Networks With a Time-Varying Malicious Agent Set. IEEE Trans. Autom. Control. 70(5): 3308-3315 (2025) - [j11]Lei Xin, Lintao Ye, George Chiu, Shreyas Sundaram:
Learning Dynamical Systems by Leveraging Data From Similar Systems. IEEE Trans. Autom. Control. 70(7): 4833-4840 (2025) - [j10]Ming Chi, Ankang Zhang, Xiaoling Wang, Lintao Ye:
Interval Observer-Based Control of Takagi-Sugeno Fuzzy Systems With Uncertainties. IEEE Trans. Fuzzy Syst. 33(7): 2136-2147 (2025) - [j9]Xueyu Ye, Zhi-Wei Liu, Ming Chi, Lintao Ye, Chaojie Li:
Real-Time Price-Based Demand Response for Industrial Manufacturing Process via Safe Reinforcement Learning. IEEE Trans. Ind. Informatics 21(4): 2937-2946 (2025) - [i17]Leonardo F. Toso, Lintao Ye, James Anderson:
Learning Stabilizing Policies via an Unstable Subspace Representation. CoRR abs/2505.01348 (2025) - [i16]Kyung-bin Kwon, Lintao Ye, Vijay Gupta, Hao Zhu:
Communication-aware Wide-Area Damping Control using Risk-Constrained Reinforcement Learning. CoRR abs/2509.23620 (2025) - 2024
- [j8]Lintao Ye, Ming Chi, Ruiquan Liao, Vijay Gupta:
Learning Decentralized Linear Quadratic Regulators with \({\sqrt{T}}\) Regret. SIAM J. Control. Optim. 62(6): 3341-3368 (2024) - [j7]Lintao Ye, Martin Figura, Yixuan Lin, Mainak Pal, Pranoy Das, Ji Liu, Vijay Gupta:
Resilient Multiagent Reinforcement Learning With Function Approximation. IEEE Trans. Autom. Control. 69(12): 8497-8512 (2024) - [c12]Andrés C. Castillo J., Ege C. Kaya, Lintao Ye, Abolfazl Hashemi:
Equitable Client Selection in Federated Learning via Truncated Submodular Maximization. CDC 2024: 5496-5502 - [c11]Lintao Ye, Aritra Mitra, Vijay Gupta:
On the Convergence of Policy Gradient for Designing a Linear Quadratic Regulator by Leveraging a Proxy System. CDC 2024: 6016-6021 - [c10]Aritra Mitra, Lintao Ye, Vijay Gupta:
Towards model-free LQR control over rate-limited channels. L4DC 2024: 1253-1265 - [i15]Aritra Mitra, Lintao Ye, Vijay Gupta:
Towards Model-Free LQR Control over Rate-Limited Channels. CoRR abs/2401.01258 (2024) - [i14]Andrés Catalino Castillo Jiménez, Ege C. Kaya, Lintao Ye, Abolfazl Hashemi:
Submodular Maximization Approaches for Equitable Client Selection in Federated Learning. CoRR abs/2408.13683 (2024) - [i13]Lintao Ye, Zhengmiao Wang, Zhi-Wei Liu, Ming Chi, Xiaoling Wang, Housheng Su:
Online Convex Optimization with Memory and Limited Predictions. CoRR abs/2410.23574 (2024) - 2023
- [j6]Lintao Ye, Zhi-Wei Liu, Ming Chi, Vijay Gupta:
Maximization of nonsubmodular functions under multiple constraints with applications. Autom. 155: 111126 (2023) - [j5]Lintao Ye, Hao Zhu, Vijay Gupta:
On the Sample Complexity of Decentralized Linear Quadratic Regulator With Partially Nested Information Structure. IEEE Trans. Autom. Control. 68(8): 4841-4856 (2023) - [i12]Lei Xin, Lintao Ye, George Chiu, Shreyas Sundaram:
Learning Dynamical Systems by Leveraging Data from Similar Systems. CoRR abs/2302.04344 (2023) - [i11]Lintao Ye, Zhi-Wei Liu, Ming Chi, Vijay Gupta:
Maximization of Nonsubmodular Functions under Multiple Constraints with Applications. CoRR abs/2305.04254 (2023) - 2022
- [j4]Changjun Zou, Lintao Ye:
Cascaded Residual Densely Connected Network for Image Super-Resolution. KSII Trans. Internet Inf. Syst. 16(9): 2882-2903 (2022) - [j3]Lintao Ye, Philip E. Paré, Shreyas Sundaram:
Parameter Estimation in Epidemic Spread Networks Using Limited Measurements. SIAM J. Control. Optim. 60(2): S49-S74 (2022) - [c9]Lei Xin, Lintao Ye, George Chiu, Shreyas Sundaram:
Identifying the Dynamics of a System by Leveraging Data from Similar Systems. ACC 2022: 818-824 - [c8]Kyung-bin Kwon, Lintao Ye, Vijay Gupta, Hao Zhu:
Model-free Learning for Risk-constrained Linear Quadratic Regulator with Structured Feedback in Networked Systems. CDC 2022: 7260-7265 - [c7]Krishna Chaitanya Kosaraju, Lintao Ye, Vijay Gupta, Rodrigo D. Trevizan, Babu Chalamala, Raymond H. Byrne:
Dissipativity-based Voltage Control in Distribution Grids. ISGT 2022: 1-5 - [i10]Lintao Ye, Ming Chi, Zhi-Wei Liu, Vijay Gupta:
Online Actuator Selection and Controller Design for Linear Quadratic Regulation over a Finite Horizon. CoRR abs/2201.10197 (2022) - [i9]Lei Xin, Lintao Ye, George Chiu, Shreyas Sundaram:
Identifying the Dynamics of a System by Leveraging Data from Similar Systems. CoRR abs/2204.05446 (2022) - [i8]Lintao Ye, Ming Chi, Vijay Gupta:
Regret Bounds for Learning Decentralized Linear Quadratic Regulator with Partially Nested Information Structure. CoRR abs/2210.08886 (2022) - 2021
- [j2]Lintao Ye, Nathaniel Woodford, Sandip Roy, Shreyas Sundaram:
On the Complexity and Approximability of Optimal Sensor Selection and Attack for Kalman Filtering. IEEE Trans. Autom. Control. 66(5): 2146-2161 (2021) - [c6]Lintao Ye, Vijay Gupta:
Client Scheduling for Federated Learning over Wireless Networks: A Submodular Optimization Approach. CDC 2021: 63-68 - [c5]Lintao Ye, Aritra Mitra, Shreyas Sundaram:
Near-Optimal Data Source Selection for Bayesian Learning. L4DC 2021: 854-865 - [i7]Lintao Ye, Philip E. Paré, Shreyas Sundaram:
Parameter Estimation in Epidemic Spread Networks Using Limited Measurements. CoRR abs/2105.04750 (2021) - [i6]Lintao Ye, Hao Zhu, Vijay Gupta:
On the Sample Complexity of Decentralized Linear Quadratic Regulator with Partially Nested Information Structure. CoRR abs/2110.07112 (2021) - 2020
- [j1]Lintao Ye, Sandip Roy, Shreyas Sundaram:
Resilient Sensor Placement for Kalman Filtering in Networked Systems: Complexity and Algorithms. IEEE Trans. Control. Netw. Syst. 7(4): 1870-1881 (2020) - [c4]Lintao Ye, Shreyas Sundaram:
Distributed Maximization of Submodular and Approximately Submodular Functions. CDC 2020: 2979-2984 - [i5]Lintao Ye, Nathaniel Woodford, Sandip Roy, Shreyas Sundaram:
On the Complexity and Approximability of Optimal Sensor Selection and Attack for Kalman Filtering. CoRR abs/2003.11951 (2020) - [i4]Lintao Ye, Sandip Roy, Shreyas Sundaram:
Resilient Sensor Placement for Kalman Filtering in Networked Systems: Complexity and Algorithms. CoRR abs/2006.14036 (2020) - [i3]Lintao Ye, Shreyas Sundaram:
Distributed Maximization of Submodular and Approximately Submodular Functions. CoRR abs/2009.12992 (2020) - [i2]Lintao Ye, Aritra Mitra, Shreyas Sundaram:
Near-Optimal Data Source Selection for Bayesian Learning. CoRR abs/2011.10712 (2020)
2010 – 2019
- 2019
- [c3]Lintao Ye, Shreyas Sundaram:
Sensor Selection for Hypothesis Testing: Complexity and Greedy Algorithms. CDC 2019: 7844-7849 - 2018
- [c2]Lintao Ye, Sandip Roy, Shreyas Sundaram:
On the Complexity and Approximability of Optimal Sensor Selection for Kalman Filtering. ACC 2018: 5049-5054 - [c1]Lintao Ye, Sandip Roy, Shreyas Sundaram:
Optimal Sensor Placement for Kalman Filtering in Stochastically Forced Consensus Networks. CDC 2018: 6686-6691 - 2017
- [i1]Lintao Ye, Sandip Roy, Shreyas Sundaram:
On the Complexity and Approximability of Optimal Sensor Selection for Kalman Filtering. CoRR abs/1711.01920 (2017)
Coauthor Index
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