Distributed learning is envisioned as the bedrock of next-generation intelligent networks,
where intelligent agents, such as mobile devices, robots, and sensors, exchange information …

Distributed online optimization and online games have been increasingly researched in the
last decade, mostly motivated by their wide applications in sensor networks, robotics (eg …

Multi-agent systems can solve scientific issues related to complex systems that are difficult or
impossible for a single agent to solve through mutual collaboration and cooperation …

This work addresses decentralized online optimization in nonstationary environments. A
network of agents aim to track the minimizer of a global, time-varying, and convex function …

A distributed convex optimization problem over a weight-unbalanced directed network is
studied in this brief, where the global objective function is equal to the sum of strongly …

This article investigates the distributed online optimization problem over a multi-agent
network subject to local set constraints and coupled inequality constraints, which has a lot of …

There is a growing cross-disciplinary effort in the broad domain of optimization and learning
with streams of data, applied to settings where traditional batch optimization techniques …

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

In this article, we investigate a distributed online constrained optimization problem with
differential privacy where the network is modeled by an unbalanced digraph with a row …

In this paper, some efficient criteria for finite-time consensus of a class of nonsmooth opinion
dynamics over a digraph are established. The lower and upper bounds on the finite settling …