23 citations · 46 across the 13 of their papers we have counts for
13 papers
Maximization of Nonsubmodular Functions under Multiple Constraints with Applications
Lintao Ye, Zhi-Wei Liu, Ming Chi +1
We consider the problem of maximizing a monotone nondecreasing set function under multiple constraints, where the constraints are also characterized by monotone nondecreasing set f…
Learning Dynamical Systems by Leveraging Data from Similar Systems
Lei Xin, Lintao Ye, George Chiu +1
We consider the problem of learning the dynamics of a linear system when one has access to data generated by an auxiliary system that shares similar (but not identical) dynamics, i…
Learning Decentralized Linear Quadratic Regulators with Regret
Lintao Ye, Ming Chi, Ruiquan Liao +1
We propose an online learning algorithm that adaptively designs a decentralized linear quadratic regulator when the system model is unknown a priori and new data samples from a sin…
Identifying the Dynamics of a System by Leveraging Data from Similar Systems
Lei Xin, Lintao Ye, George Chiu +1
We study the problem of identifying the dynamics of a linear system when one has access to samples generated by a similar (but not identical) system, in addition to data from the t…
Model-free Learning for Risk-constrained Linear Quadratic Regulator with Structured Feedback in Networked Systems
Kyung-bin Kwon, Lintao Ye, Vijay Gupta +1
We develop a model-free learning algorithm for the infinite-horizon linear quadratic regulator (LQR) problem. Specifically, (risk) constraints and structured feedback are considere…
Online Actuator Selection and Controller Design for Linear Quadratic Regulation with Unknown System Model
Lintao Ye, Ming Chi, Zhi-Wei Liu +1
We study the simultaneous actuator selection and controller design problem for linear quadratic regulation with Gaussian noise over a finite horizon of length and unknown syste…
On the Sample Complexity of Decentralized Linear Quadratic Regulator with Partially Nested Information Structure
Lintao Ye, Hao Zhu, Vijay Gupta
We study the problem of control policy design for decentralized state-feedback linear quadratic control with a partially nested information structure, when the system model is unkn…
Parameter Estimation in Epidemic Spread Networks Using Limited Measurements
Lintao Ye, Philip E. Paré, Shreyas Sundaram
We study the problem of estimating the parameters (i.e., infection rate and recovery rate) governing the spread of epidemics in networks. Such parameters are typically estimated by…
Near-Optimal Data Source Selection for Bayesian Learning
Lintao Ye, Aritra Mitra, Shreyas Sundaram
We study a fundamental problem in Bayesian learning, where the goal is to select a set of data sources with minimum cost while achieving a certain learning performance based on the…
Distributed Maximization of Submodular and Approximately Submodular Functions
Lintao Ye, Shreyas Sundaram
We study the problem of maximizing a submodular function, subject to a cardinality constraint, with a set of agents communicating over a connected graph. We propose a distributed g…
Resilient Sensor Placement for Kalman Filtering in Networked Systems: Complexity and Algorithms
Lintao Ye, Sandip Roy, Shreyas Sundaram
Given a linear dynamical system affected by noise, we study the problem of optimally placing sensors (at design-time) subject to a sensor placement budget constraint in order to mi…
On the Complexity and Approximability of Optimal Sensor Selection and Attack for Kalman Filtering
Lintao Ye, Nathaniel Woodford, Sandip Roy +1
Given a linear dynamical system affected by stochastic noise, we consider the problem of selecting an optimal set of sensors (at design-time) to minimize the trace of the steady st…
On the Complexity and Approximability of Optimal Sensor Selection for Kalman Filtering
Lintao Ye, Sandip Roy, Shreyas Sundaram
Given a linear dynamical system, we consider the problem of selecting (at design-time) an optimal set of sensors (subject to certain budget constraints) to minimize the trace of th…