This paper considers the problem of solving distributed online optimization over a network
that consists of multiple interacting nodes. Each node in the network is endowed with a …

This article examines an online distributed optimization problem over an unbalanced
digraph, in which a group of nodes in the network tries to collectively search for a minimizer …

Decentralized optimization methods often entail information exchange between neighbors.
In many circumstances, due to the limited communication bandwidth, the exchanged …

In this article, we concentrate on distributed online convex optimization problems over
multiagent systems, where the communication between nodes is represented by a class of …

This work is concerned with distributed online bandit learning over a multi-agent network,
where a group of agents aim to seek the minimizer of a time-changing global loss function …

In this article, we consider distributed online convex optimization problems, where the
distributed system consists of various computing units connected through a time-varying …

The paper deals with online distributed convex optimization over a multi-agent network,
where a swarm of agents attempts to minimize coordinately a sequence of time-changing …

Decentralized multi-agent optimization usually relies on information exchange between
neighboring agents, which can incur unaffordable communication overhead in practice. To …

Decentralized optimization methods often entail information exchange between neighbors.
Transmission failures can happen due to network congestion, hardware/software issues …

We study distributed methods for online prediction and stochastic optimization. Our
approach is iterative: In each round, nodes first perform local computations and then …