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 …

In this paper, we study the dynamic regret of online linear quadratic regulator (LQR) control
with time-varying cost functions and disturbances. We consider the case where a finite look …

This article considers online optimization with a finite prediction window of cost functions
and additional switching costs on the decisions. We study the fundamental limits of dynamic …

This paper considers online optimal control with affine constraints on the states and actions
under linear dynamics with bounded random disturbances. The system dynamics and …

We consider control in linear time-varying dynamical systems from the perspective of regret
minimization. Unlike most prior work in this area, we focus on the problem of designing an …

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 …

We examine the problem of smoothed online optimization, where a decision maker must
sequentially choose points in a normed vector space to minimize the sum of per-round, non …

We examine the problem of online optimization, where a decision maker must sequentially
choose points in a general metric space to minimize the sum of per-round, non-convex …

Online optimization with memory costs has many real-world applications, where sequential
actions are made without knowing the future input. Nonetheless, the memory cost couples …

In this paper, we investigate an online prediction strategy named as Discounted-Normal-
Predictor [Kapralov and Panigrahy, 2010] for smoothed online convex optimization (SOCO) …