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 …

By enabling multiple agents to cooperatively solve a global optimization problem in the
absence of a central coordinator, decentralized stochastic optimization is gaining increasing …

Distributed optimization enables networked agents to cooperatively solve a global
optimization problem. Despite making significant inroads, most existing results on distributed …

This paper focuses on investigating the nonsmooth resource allocation problem based on
distributed dynamical systems over state-dependent communication networks. Taking into …

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 …

Privacy protection and nonconvexity are two challenging problems in decentralized
optimization and learning involving sensitive data. Despite some recent advances …

This article investigates constrained online noncooperative games (NGs) of multiagent
systems over unbalanced digraphs, where the cost functions of players are time-varying and …

In this paper, we study distributed constrained online convex optimization for a wireless
system consisting of a parameter server and multiple agents. Each agent has a local …

Due to the iterative information exchange between agents, decentralized multi-agent
optimization algorithms often incur large communication overhead, which is not affordable in …