Ting-Jui Chang

According to our database, Ting-Jui Chang authored at least 12 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Regret Analysis of Distributed Online LQR Control for Unknown LTI Systems.

Ting-Jui Chang, Shahin Shahrampour

IEEE Trans. Autom. Control., January, 2024

Regret Analysis of Policy Optimization over Submanifolds for Linearly Constrained Online LQG.

Ting-Jui Chang, Shahin Shahrampour

CoRR, 2024

2023

Regret Analysis of Distributed Online Control for LTI Systems with Adversarial Disturbances.

Ting-Jui Chang, Shahin Shahrampour

CoRR, 2023

Dynamic Regret Analysis of Safe Distributed Online Optimization for Convex and Non-convex Problems.

Ting-Jui Chang, Sapana Chaudhary, Dileep Kalathil, Shahin Shahrampour

CoRR, 2023

2022

RFN: A Random-Feature Based Newton Method for Empirical Risk Minimization in Reproducing Kernel Hilbert Spaces.

Ting-Jui Chang, Shahin Shahrampour

IEEE Trans. Signal Process., 2022

Distributed Online System Identification for LTI Systems Using Reverse Experience Replay.

Ting-Jui Chang, Shahin Shahrampour

Proceedings of the 61st IEEE Conference on Decision and Control, 2022

2021

Distributed Online Linear Quadratic Control for Linear Time-invariant Systems.

Ting-Jui Chang, Shahin Shahrampour

Proceedings of the 2021 American Control Conference, 2021

On Online Optimization: Dynamic Regret Analysis of Strongly Convex and Smooth Problems.

Ting-Jui Chang, Shahin Shahrampour

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Unconstrained Online Optimization: Dynamic Regret Analysis of Strongly Convex and Smooth Problems.

Ting-Jui Chang, Shahin Shahrampour

CoRR, 2020

A Random-Feature Based Newton Method for Empirical Risk Minimization in Reproducing Kernel Hilbert Space.

Shahin Shahrampour, Ting-Jui Chang

CoRR, 2020

Global Convergence of Newton Method for Empirical Risk Minimization in Reproducing Kernel Hilbert Space.

Ting-Jui Chang, Shahin Shahrampour

Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020

2018

Efficient Two-Step Adversarial Defense for Deep Neural Networks.

Ting-Jui Chang, Yukun He, Peng Li

CoRR, 2018