5 citations · 5 across the 8 of their papers we have counts for
8 papers
Learning Linearized Models from Nonlinear Systems under Initialization Constraints with Finite Data
Lei Xin, Baike She, Qi Dou +2
The identification of a linear system model from data has wide applications in control theory. The existing work that provides finite sample guarantees for linear system identifica…
Classification with a Network of Partially Informative Agents: Enabling Wise Crowds from Individually Myopic Classifiers
Tong Yao, Shreyas Sundaram
We consider the problem of classification with a (peer-to-peer) network of heterogeneous and partially informative agents, each receiving local data generated by an underlying true…
Control of SIR Epidemics: Sacrificing Optimality for Feasibility
Baike She, Lei Xin, Shreyas Sundaram +1
We study the impact of parameter estimation and state measurement errors on a control framework for optimally mitigating the spread of epidemics. We capture the epidemic spreading…
C3D: Cascade Control with Change Point Detection and Deep Koopman Learning for Autonomous Surface Vehicles
Jianwen Li, Hyunsang Park, Wenjian Hao +10
In this paper, we discuss the development and deployment of a robust autonomous system capable of performing various tasks in the maritime domain under unknown dynamic conditions.…
Online Change Points Detection for Linear Dynamical Systems with Finite Sample Guarantees
Lei Xin, George Chiu, Shreyas Sundaram
The problem of online change point detection is to detect abrupt changes in properties of time series, ideally as soon as possible after those changes occur. Existing work on onlin…
Reverse Engineering the Reproduction Number: A Framework for Data-Driven Counterfactual Analysis, Strategy Evaluation, and Feedback Control of Epidemics
Baike She, Rebecca Lee Smith, Ian Pytlarz +2
During the COVID-19 pandemic, different countries, regions, and communities constructed various epidemic models to evaluate spreading behaviors and assist in making mitigation poli…
Robust Online Covariance and Sparse Precision Estimation Under Arbitrary Data Corruption
Tong Yao, Shreyas Sundaram
Gaussian graphical models are widely used to represent correlations among entities but remain vulnerable to data corruption. In this work, we introduce a modified trimmed-inner-pro…
Learning Linearized Models from Nonlinear Systems with Finite Data
Lei Xin, George Chiu, Shreyas Sundaram
Identifying a linear system model from data has wide applications in control theory. The existing work on finite sample analysis for linear system identification typically uses dat…