3 citations · 6 across the 8 of their papers we have counts for
8 papers
Projected Gradient Descent for Constrained Decision-Dependent Optimization
Zifan Wang, Changxin Liu, Thomas Parisini +2
This paper considers the decision-dependent optimization problem, where the data distributions react in response to decisions affecting both the objective function and linear const…
Distributed model predictive control without terminal cost under inexact distributed optimization
Xiaoyu Liu, Dimos V. Dimarogonas, Changxin Liu +2
This paper presents a novel distributed model predictive control (MPC) formulation without terminal cost and a corresponding distributed synthesis approach for distributed linear d…
Privacy-Preserving Set-Based Estimation Using Differential Privacy and Zonotopes
Mohammed M. Dawoud, Changxin Liu, Karl H. Johansson +1
For large-scale cyber-physical systems, the collaboration of spatially distributed sensors is often needed to perform the state estimation process. Privacy concerns arise from disc…
Achieving violation-free distributed optimization under coupling constraints
Changxin Liu, Xiao Tan, Xuyang Wu +2
Constraint satisfaction is a critical component in a wide range of engineering applications, including but not limited to safe multi-agent control and economic dispatch in power sy…
A continuous-time violation-free multi-agent optimization algorithm and its applications to safe distributed control
Xiao Tan, Changxin Liu, Karl H. Johansson +1
In this work, we propose a continuous-time distributed optimization algorithm with guaranteed zero coupling constraint violation and apply it to safe distributed control in the pre…
Asynchronous Distributed Optimization with Delay-free Parameters
Xuyang Wu, Changxin Liu, Sindri Magnusson +1
Existing asynchronous distributed optimization algorithms often use diminishing step-sizes that cause slow practical convergence, or use fixed step-sizes that depend on and decreas…
Constrained Optimization with Decision-Dependent Distributions
Zifan Wang, Changxin Liu, Thomas Parisini +2
In this paper we deal with stochastic optimization problems where the data distributions change in response to the decision variables. Traditionally, the study of optimization prob…
Distributed Empirical Risk Minimization With Differential Privacy
Changxin Liu, Karl H. Johansson, Yang Shi
This work studies the distributed empirical risk minimization (ERM) problem under differential privacy (DP) constraint. Standard distributed algorithms achieve DP typically by pert…