Online Caching with no Regret: Optimistic Learning via Recommendations

May 1, 2024·
Naram Mhaisen
Naram Mhaisen
,
George Iosifidis
,
Douglas J. Leith
Abstract
We design online caching algorithms that exploit (possibly inaccurate) predictions from a recommender to achieve provably better regret than prediction-oblivious schemes, while retaining worst-case no-regret guarantees when predictions are adversarial.
Type
Publication
IEEE Transactions on Mobile Computing, 23(5):5949-5965
publications
Online Learning Caching Optimistic Learning
Naram Mhaisen
Authors
Naram Mhaisen
Postdoctoral Researcher

Naram is a Postdoctoral Researcher with the Networked Systems Group at the Faculty of Electrical Engineering, Mathematics, and Computer Science, TU Delft, The Netherlands. His research focuses on online learning techniques with applications in resource management across communication systems.

He received the B.Sc. degree in Computer Engineering from Qatar University in 2017 with the Order of Excellence award, and the M.Sc. degree with Distinction in Computing from Qatar University in 2020, supervised by Prof. Mohsen Guizani. He completed his Ph.D. at TU Delft in 2025, supervised by Dr. George Iosifidis, with a thesis on Optimistic Learning with Applications to Caching Networks.

His work has been recognized by the Microsoft Imagine Cup award (2017) and a NEC Europe Research Fellowship (2022).