9 citations · 18 across the 12 of their papers we have counts for
12 papers
A Stochastic Second-Order Proximal Method for Distributed Optimization
Chenyang Qiu, Shanying Zhu, Zichong Ou +1
In this paper, we propose a distributed stochastic second-order proximal method that enables agents in a network to cooperatively minimize the sum of their local loss functions wit…
Decentralized Statistical Inference with Unrolled Graph Neural Networks
He Wang, Yifei Shen, Ziyuan Wang +4
In this paper, we investigate the decentralized statistical inference problem, where a network of agents cooperatively recover a (structured) vector from private noisy samples with…
Distributed Optimization with Coupling Constraints
Xuyang Wu, He Wang, Jie Lu
In this paper, we develop a novel distributed algorithm for addressing convex optimization with both nonlinear inequality and linear equality constraints, where the objective funct…
A Unifying Approximate Method of Multipliers for Distributed Composite Optimization
Xuyang Wu, Jie Lu
This paper investigates solving convex composite optimization on an undirected network, where each node, privately endowed with a smooth component function and a nonsmooth one, is…
Decentralized Approximate Newton Methods for Convex Optimization on Networked Systems
Hejie Wei, Zhihai Qu, Xuyang Wu +2
In this paper, a class of Decentralized Approximate Newton (DEAN) methods for addressing convex optimization on a networked system are developed, where nodes in the networked syste…
Fenchel Dual Gradient Methods for Distributed Convex Optimization over Time-varying Networks
Xuyang Wu, Jie Lu
In the large collection of existing distributed algorithms for convex multi-agent optimization, only a handful of them provide convergence rate guarantees on agent networks with ti…
Relaxed Connected Dominating Set Problem with Application to Secure Power Network Design
Kin Cheong Sou, Jie Lu
This paper investigates a combinatorial optimization problem motived from a secure power network design application in [Dán and Sandberg 2010]. Two equivalent graph optimization fo…
Convergence analysis of approximate primal solutions in dual first-order methods
Jie Lu, Mikael Johansson
Dual first-order methods are powerful techniques for large-scale convex optimization. Although an extensive research effort has been devoted to studying their convergence propertie…
A Distributed Algorithm for Solving Positive Definite Linear Equations over Networks with Membership Dynamics
Jie Lu, Choon Yik Tang
This paper considers the problem of solving a symmetric positive definite system of linear equations over a network of agents with arbitrary asynchronous interactions and membershi…
Zero-Gradient-Sum Algorithms for Distributed Convex Optimization: The Continuous-Time Case
Jie Lu, Choon Yik Tang
This paper presents a set of continuous-time distributed algorithms that solve unconstrained, separable, convex optimization problems over undirected networks with fixed topologies…
Controlled Hopwise Averaging: Bandwidth/Energy-Efficient Asynchronous Distributed Averaging for Wireless Networks
Choon Yik Tang, Jie Lu
This paper addresses the problem of averaging numbers across a wireless network from an important, but largely neglected, viewpoint: bandwidth/energy efficiency. We show that exist…
Gossip Algorithms for Convex Consensus Optimization over Networks
Jie Lu, Choon Yik Tang, Paul R. Regier +1
In many applications, nodes in a network desire not only a consensus, but an optimal one. To date, a family of subgradient algorithms have been proposed to solve this problem under…