Decentralized solutions to finite-sum minimization are of significant importance in many
signal processing, control, and machine learning applications. In such settings, the data is …

We consider an unconstrained distributed optimization problem and assume that the bit rate
of the communication in the network is limited. We propose a distributed optimization …

In this paper, we consider distributed optimization problems where agents, each possessing
a local cost function, collaboratively minimize the average of the local cost functions over a …

This article studies the distributed online stochastic convex optimization problem with the
time-varying constraint over a multiagent system constructed by various agents. The …

We consider the distributed optimization problem where agents, each possessing a local
cost function, collaboratively minimize the average of the cost functions over a connected …

We present a novel distributed algorithm for convex constrained optimization problems that
are subject to noise corruption and uncertainties. The proposed scheme can be classified as …

We study distributed stochastic gradient (D-SG) method and its accelerated variant (D-ASG)
for solving decentralized strongly convex stochastic optimization problems where the …

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

We study distributed optimization problems over a network when the communication
between the nodes is constrained, and so information that is exchanged between the nodes …

Distributed optimization enables networked agents to cooperatively solve a global
optimization problem. Despite making significant inroads, most existing results on distributed …