38 citations · 49 across the 11 of their papers we have counts for
11 papers
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…
Delay-agnostic Asynchronous Distributed Optimization
Xuyang Wu, Changxin Liu, Sindri Magnusson +1
Existing asynchronous distributed optimization algorithms often use diminishing step-sizes that cause slow practical convergence, or fixed step-sizes that depend on an assumed uppe…
Rate analysis of dual averaging for nonconvex distributed optimization
Changxin Liu, Xuyang Wu, Xinlei Yi +2
This work studies nonconvex distributed constrained optimization over stochastic communication networks. We revisit the distributed dual averaging algorithm, which is known to conv…
Secure State Estimation against Sparse Attacks on a Time-varying Set of Sensors
Zishuo Li, Muhammad Umar B. Niazi, Changxin Liu +2
This paper studies the problem of secure state estimation of a linear time-invariant (LTI) system with bounded noise in the presence of sparse attacks on an unknown, time-varying s…
A Robust Distributed Model Predictive Control Framework for Consensus of Multi-Agent Systems with Input Constraints and Varying Delays
Henglai Wei, Changxin Liu, Yang Shi
This paper studies the consensus problem of general linear discrete-time multi-agent systems (MAS) with input constraints and bounded time-varying communication delays. We propose…
Decentralized Composite Optimization in Stochastic Networks: A Dual Averaging Approach with Linear Convergence
Changxin Liu, Zirui Zhou, Jian Pei +2
Decentralized optimization, particularly the class of decentralized composite convex optimization (DCCO) problems, has found many applications. Due to ubiquitous communication cong…
Accelerated Dual Averaging Methods for Decentralized Constrained Optimization
Changxin Liu, Yang Shi, Huiping Li +1
In this work, we study decentralized convex constrained optimization problems in networks. We focus on the dual averaging-based algorithmic framework that is well-documented to be…
Self-Triggered Adaptive Model Predictive Control of Constrained Nonlinear Systems: A Min-Max Approach
Kunwu Zhang, Changxin Liu, Yang Shi
In this paper, a self-triggered adaptive model predictive control (MPC) algorithm is proposed for constrained discrete-time nonlinear systems subject to parametric uncertainties an…
Towards an convergence rate for distributed dual averaging
Changxin Liu, Huiping Li, Yang Shi
Recently, distributed dual averaging has received increasing attention due to its superiority in handling constraints and dynamic networks in multiagent optimization. However, all…
Resource-aware Exact Decentralized Optimization Using Event-triggered Broadcasting
Changxin Liu, Huiping Li, Yang Shi
This work addresses the decentralized optimization problem where a group of agents with coupled private objective functions work together to exactly optimize the summation of local…
A unitary distributed subgradient method for multi-agent optimization with different coupling sources
Changxin Liu, Huiping Li, Yang Shi
In this work, we first consider distributed convex constrained optimization problems where the objective function is encoded by multiple local and possibly nonsmooth objectives pri…