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 …

Decentralized stochastic optimization methods have gained a lot of attention recently, mainly
because of their cheap per iteration cost, data locality, and their communication-efficiency. In …

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 …

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 …

In this paper, we study the problem of distributed multi-agent optimization over a network,
where each agent possesses a local cost function that is smooth and strongly convex. The …

This paper presents an asynchronous gossip-based algorithm for finding a Nash equilibrium
(NE) of a game in a distributed multi-player network. The algorithm is designed in such a …

Convergent sequences of real numbers play a fundamental role in many different problems
in system theory, eg, in Lyapunov stability analysis, as well as in optimization theory and …

The presence of embedded electronics and communication capabilities as well as sensing
and control in smart devices has given rise to the novel concept of cyber-physical networks …

We provide a unifying framework for distributed convex optimization over time-varying
networks, in the presence of constraints and uncertainty, features that are typically treated …

This paper deals with an optimization problem over a network of agents, where the cost
function is the sum of the individual (possibly nonsmooth) objectives of the agents and the …