Mathematical optimization is one of the cornerstones of modern engineering research and
practice. Yet, throughout all application domains, mathematical optimization is, for the most …

Optimization underpins many of the challenges that science and technology face on a daily
basis. Recent years have witnessed a major shift from traditional optimization paradigms …

We build a theoretical framework for designing and understanding practical meta-learning
methods that integrates sophisticated formalizations of task-similarity with the extensive …

In a multi-armed bandit (MAB) problem a gambler needs to choose at each round of play
one of K arms, each characterized by an unknown reward distribution. Reward realizations …

In this article, online noncooperative games without full decision information are studied,
where the goal of players is to seek the Nash equilibria in a distributed manner. Different …

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 …

In this paper, we study online convex optimization in dynamic environments, and aim to
bound the dynamic regret with respect to any sequence of comparators. Existing work have …

Existing approaches to online convex optimization make sequential one-slot-ahead
decisions, which lead to (possibly adversarial) losses that drive subsequent decision …

In this paper, we address tracking of a time-varying parameter with unknown dynamics. We
formalize the problem as an instance of online optimization in a dynamic setting. Using …

In online advertising markets, advertisers often purchase ad placements through bidding in
repeated auctions based on realized viewer information. We study how budget-constrained …