185 citations · 375 across the 16 of their papers we have counts for
5 papers · 1 filter
Optimistic No-regret Algorithms for Discrete Caching
Naram Mhaisen, Abhishek Sinha, Georgios Paschos +1
We take a systematic look at the problem of storing whole files in a cache with limited capacity in the context of optimistic learning, where the caching policy has access to a pre…
Online Caching with no Regret: Optimistic Learning via Recommendations
Naram Mhaisen, George Iosifidis, Douglas Leith
The design of effective online caching policies is an increasingly important problem for content distribution networks, online social networks and edge computing services, among ot…
Multi-Agent Reinforcement Learning for Network Selection and Resource Allocation in Heterogeneous multi-RAT Networks
Mhd Saria Allahham, Alaa Awad Abdellatif, Naram Mhaisen +3
The rapid production of mobile devices along with the wireless applications boom is continuing to evolve daily. This motivates the exploitation of wireless spectrum using multiple…
Online Caching with Optimistic Learning
Naram Mhaisen, George Iosifidis, Douglas Leith
The design of effective online caching policies is an increasingly important problem for content distribution networks, online social networks and edge computing services, among ot…
Exploring Deep Reinforcement Learning-Assisted Federated Learning for Online Resource Allocation in Privacy-Persevering EdgeIoT
Jingjing Zheng, Kai Li, Naram Mhaisen +3
Federated learning (FL) has been increasingly considered to preserve data training privacy from eavesdropping attacks in mobile edge computing-based Internet of Thing (EdgeIoT). On…