A 2-competitive algorithm for online convex optimization with switching costs
We consider a natural online optimization problem set on the real line. The state of the
online algorithm at each integer time is a location on the real line. At each integer time, a …
online algorithm at each integer time is a location on the real line. At each integer time, a …
A nearly-linear bound for chasing nested convex bodies
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 …
between geometry and competitive ratio in metrical task systems. In convex body chasing, at …
Competitive online optimization under inventory constraints
This paper studies online optimization under inventory (budget) constraints. While online
optimization is a well-studied topic, versions with inventory constraints have proven difficult …
optimization is a well-studied topic, versions with inventory constraints have proven difficult …
Chasing convex bodies and functions
We consider three related online problems: Online Convex Optimization, Convex Body
Chasing, and Lazy Convex Body Chasing. In Online Convex Optimization the input is an …
Chasing, and Lazy Convex Body Chasing. In Online Convex Optimization the input is an …
Competitive online optimization with multiple inventories: A divide-and-conquer approach
We study an online inventory trading problem where a user seeks to maximize the
aggregate revenue of trading multiple inventories over a time horizon. The trading …
aggregate revenue of trading multiple inventories over a time horizon. The trading …
Dealing with transaction costs in portfolio optimization: Online gradient descent with momentum
Outperforming the markets through active investment strategies is one of the main
challenges in finance. The random movements of assets and the unpredictability of catalysts …
challenges in finance. The random movements of assets and the unpredictability of catalysts …
Understand dynamic regret with switching cost for online decision making
As a metric to measure the performance of an online method, dynamic regret with switching
cost has drawn much attention for online decision making problems. Although the sublinear …
cost has drawn much attention for online decision making problems. Although the sublinear …
Near-optimal adversarial reinforcement learning with switching costs
Switching costs, which capture the costs for changing policies, are regarded as a critical
metric in reinforcement learning (RL), in addition to the standard metric of losses (or …
metric in reinforcement learning (RL), in addition to the standard metric of losses (or …
Adaptive model predictive control of autonomic distributed parallel computations with variable horizons and switching costs
G Mencagli - Concurrency and Computation: Practice and …, 2016 - Wiley Online Library
Autonomic computing is a paradigm for building systems capable of adapting their operation
when external changes occur, such as workload variations, load surges and changes in the …
when external changes occur, such as workload variations, load surges and changes in the …
Adversarial Online Reinforcement Learning Under Limited Defender Resources
Reinforcement learning (RL) is a very powerful tool for sequential decision making. It has
already been a vital component in solving grand challenge problems like the “protein folding …
already been a vital component in solving grand challenge problems like the “protein folding …