We study\emph {smoothed online convex optimization}, a version of online convex
optimization where the learner incurs a penalty for changing her actions between rounds …

In the chasing convex bodies problem, an online player receives a request sequence of N
convex sets K 1,…, KN contained in a normed space X of dimension d. The player starts at x …

We study online optimization in a setting where an online learner seeks to optimize a per-
round hitting cost, which may be non-convex, while incurring a movement cost when …

We study the problem of chasing convex bodies online: given a sequence of convex bodies
the algorithm must respond with points in an online fashion (ie, is chosen before is …

In this paper, we revisit the problem of smoothed online learning, in which the online learner
suffers both a hitting cost and a switching cost, and target two performance metrics …

Many real-world control systems, such as the smart grid and software defined networks,
have decentralized components that react quickly using local information and centralized …

Let F be a family of sets in some metric space. In the F-chasing problem, an online algorithm
observes a request sequence of sets in F and responds (online) by giving a sequence of …

Friedman and Linial [8] introduced the convex body chasing problem to explore the interplay
between geometry and competitive ratio in metrical task systems. In convex body chasing, at …

We investigate the problem of stabilizing an unknown networked linear system under
communication constraints and adversarial disturbances. We propose the first provably …

This paper studies online optimization under inventory (budget) constraints. While online
optimization is a well-studied topic, versions with inventory constraints have proven difficult …