We consider a distributed convex optimization problem in a network which is time-varying
and not always strongly connected. The local cost function of each node is affected by some …

We study a standard distributed optimization framework where N networked nodes
collaboratively minimize the sum of their local convex costs. The main body of existing work …

In this paper, we consider a distributed stochastic non-convex optimization problem, which is
about minimizing a sum of $ n $ local cost functions over a network with only zeroth-order …

In this paper we consider a distributed stochastic optimization problem without the
gradient/subgradient information for the local objective functions, subject to local convex …

In this paper, we study distributed stochastic optimization to minimize a sum of smooth and
strongly-convex local cost functions over a network of agents, communicating over a strongly …

In this paper, we consider a stochastic distributed nonconvex optimization problem with the
cost function being distributed over n agents having access only to zeroth-order (ZO) …

We examine fundamental tradeoffs in iterative distributed zeroth and first order stochastic
optimization in multi-agent networks in terms of\emph {communication cost}(number of per …

This paper considers a distributed stochastic strongly convex optimization, where agents
connected over a network aim to cooperatively minimize the average of all agents' local cost …

We consider a distributed stochastic optimization problem that is solved by a decentralized
network of agents with only local communication between neighboring agents. The goal of …

Motivated by broad applications in computer science and engineering, we study distributed
algorithms for optimization problems over a network of nodes, where the goal is to optimize …