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

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 study online learning problems in which a decision maker has to take a sequence of
decisions subject to $ m $ long-term constraints. The goal of the decision maker is to …

This paper considers online convex optimization with hard constraints and analyzes
achievable regret and cumulative hard constraint violation (violation for short). The problem …

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 …

Distributed bandit online convex optimization with time-varying coupled inequality
constraints is considered, motivated by a repeated game between a group of learners and …

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

Mobile-Edge Computing (MEC) is an emerging paradigm in the Internet of Vehicles (IoV) to
meet the ever-increasing computation demands of smart applications. To provide …

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

We study a repeated persuasion setting between a sender and a receiver, where at each
time t, the sender shares information about a payoff-relevant state with the receiver. The …