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 …

Traditionally, offline optimization of power systems is acceptable due to the largely
predictable loads and reliable generation. The increasing penetration of fluctuating …

This paper presents a novel active fault tolerance framework for uncertain high-order fully-
actuated systems (HOFASs). Starting from the uncertain faulty HOFAS model with nonlinear …

This article investigates distributed online convex optimization in the presence of an
aggregative variable without any global/central coordinators over a multiagent network. In …

This article proposes a new framework for distributed optimization, called distributed
aggregative optimization, which allows local objective functions to be dependent not only on …

This paper considers online convex optimization with long term constraints, where
constraints can be violated in intermediate rounds, but need to be satisfied in the long run …

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 …

Renewable energy integration is an effective measure to resolve environmental problems
and implement sustainable development, yet the volatility of wind and solar generation has …

We investigate online nonconvex optimization from a local regret minimization perspective.
Previous studies along this line implicitly required the access to sufficient gradient oracles at …

Heart disease is a leading global cause of death, while federated learning (FL) is an
effective way to predict it. Due to patient privacy concerns and the centralized nature of …