3 citations · 6 across the 5 of their papers we have counts for
5 papers
A survey on secure decentralized optimization and learning
Changxin Liu, Nicola Bastianello, Wei Huo +2
Decentralized optimization has become a standard paradigm for solving large-scale decision-making problems and training large machine learning models without centralizing data. How…
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…
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…
Delay-agnostic Asynchronous Coordinate Update Algorithm
Xuyang Wu, Changxin Liu, Sindri Magnusson +1
We propose a delay-agnostic asynchronous coordinate update algorithm (DEGAS) for computing operator fixed points, with applications to asynchronous optimization. DEGAS includes nov…
Differentially Private Set-Based Estimation Using Zonotopes
Mohammed M. Dawoud, Changxin Liu, Amr Alanwar +1
For large-scale cyber-physical systems, the collaboration of spatially distributed sensors is often needed to perform the state estimation process. Privacy concerns naturally arise…