Online Caching with Optimistic Learning

The design of effective online caching policies is an increasingly important problem for content distribution networks, online social networks and edge computing services, among other areas. This paper proposes a new algorithmic toolbox for tackling this problem through the lens of optimistic online...

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Bibliographic Details

Published in:	arXiv.org
Main Authors:	Mhaisen, Naram, Iosifidis, George, Leith, Douglas
Format:	Paper
Language:	English
Published:	Ithaca Cornell University Library, arXiv.org 20.04.2022
Subjects:	Algorithms Caching Decision theory Design optimization Distance learning Edge computing Machine learning Policies Recommender systems Social networks
ISSN:	2331-8422
Online Access:	Get full text
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