In distributed optimization of multi-agent systems, agents cooperate to minimize a global
function which is a sum of local objective functions. Motivated by applications including …

Advances in wired and wireless technology have necessitated the development of theory,
models, and tools to cope with the new challenges posed by large-scale control and …

In decentralized optimization, nodes cooperate to minimize an overall objective function that
is the sum (or average) of per-node private objective functions. Algorithms interleave local …

Multi-agent distributed consensus optimization problems arise in many signal processing
applications. Recently, the alternating direction method of multipliers (ADMM) has been …

This technical note presents a continuous-time multi-agent system for distributed
optimization with an additive objective function composed of individual objective functions …

We present a new class of decentralized first-order methods for nonsmooth and stochastic
optimization problems defined over multiagent networks. Considering that communication is …

In this paper, distributed optimization is addressed based on a continuous-time multiagent
system in the presence of time-varying communication delays. First, the relationship …

We study distributed optimization in a cooperative multi-agent setting, where agents have to
agree on the usage of shared resources and can communicate via a time-varying network to …

A distributed algorithm is described for solving a linear algebraic equation of the form
assuming the equation has at least one solution. The equation is simultaneously solved by …

Federated learning has generated significant interest, with nearly all works focused on a
“star” topology where nodes/devices are each connected to a central server. We migrate …