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 …

This paper considers the problem of distributed optimization over time-varying graphs. For
the case of undirected graphs, we introduce a distributed algorithm, referred to as DIGing …

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 …

There has been a growing effort in studying the distributed optimization problem over a
network. The objective is to optimize a global function formed by a sum of local functions …

In this article, we focus on solving a distributed convex optimization problem in a network,
where each agent has its own convex cost function and the goal is to minimize the sum of …

Technological advances in ad hoc networking and the availability of low-cost reliable
computing, data storage, and sensing devices have made scenarios possible where the …

In this letter, we study distributed optimization, where a network of agents, abstracted as a
directed graph, collaborates to minimize the average of locally known convex functions …

This paper proposes a novel proximal-gradient algorithm for a decentralized optimization
problem with a composite objective containing smooth and nonsmooth terms. Specifically …

This paper considers the distributed optimization problem over a network, where the
objective is to optimize a global function formed by a sum of local functions, using only local …