Lintao Ye

Orcid: 0000-0001-8608-5815

According to our database1, Lintao Ye authored at least 22 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Links

On csauthors.net:

Bibliography

2024
Resilient Multiagent Reinforcement Learning With Function Approximation.
IEEE Trans. Autom. Control., December, 2024

Online Convex Optimization with Memory and Limited Predictions.
CoRR, 2024

Submodular Maximization Approaches for Equitable Client Selection in Federated Learning.
CoRR, 2024

Towards model-free LQR control over rate-limited channels.
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, 2024

2023
Maximization of nonsubmodular functions under multiple constraints with applications.
Autom., September, 2023

On the Sample Complexity of Decentralized Linear Quadratic Regulator With Partially Nested Information Structure.
IEEE Trans. Autom. Control., August, 2023

Learning Dynamical Systems by Leveraging Data from Similar Systems.
CoRR, 2023

2022
Parameter Estimation in Epidemic Spread Networks Using Limited Measurements.
SIAM J. Control. Optim., 2022

Cascaded Residual Densely Connected Network for Image Super-Resolution.
KSII Trans. Internet Inf. Syst., 2022

Regret Bounds for Learning Decentralized Linear Quadratic Regulator with Partially Nested Information Structure.
CoRR, 2022

Online Actuator Selection and Controller Design for Linear Quadratic Regulation over a Finite Horizon.
CoRR, 2022

Dissipativity-based Voltage Control in Distribution Grids.
Proceedings of the 2022 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference, 2022

Model-free Learning for Risk-constrained Linear Quadratic Regulator with Structured Feedback in Networked Systems.
Proceedings of the 61st IEEE Conference on Decision and Control, 2022

Identifying the Dynamics of a System by Leveraging Data from Similar Systems.
Proceedings of the American Control Conference, 2022

2021
On the Complexity and Approximability of Optimal Sensor Selection and Attack for Kalman Filtering.
IEEE Trans. Autom. Control., 2021

Near-Optimal Data Source Selection for Bayesian Learning.
Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

Client Scheduling for Federated Learning over Wireless Networks: A Submodular Optimization Approach.
Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

2020
Resilient Sensor Placement for Kalman Filtering in Networked Systems: Complexity and Algorithms.
IEEE Trans. Control. Netw. Syst., 2020

Distributed Maximization of Submodular and Approximately Submodular Functions.
Proceedings of the 59th IEEE Conference on Decision and Control, 2020

2019
Sensor Selection for Hypothesis Testing: Complexity and Greedy Algorithms.
Proceedings of the 58th IEEE Conference on Decision and Control, 2019

2018
Optimal Sensor Placement for Kalman Filtering in Stochastically Forced Consensus Networks.
Proceedings of the 57th IEEE Conference on Decision and Control, 2018

On the Complexity and Approximability of Optimal Sensor Selection for Kalman Filtering.
Proceedings of the 2018 Annual American Control Conference, 2018


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