most citedA Federated Learning Scheme for Neuro-developmental Disorders: Multi-Aspect ASD Detection

4 citations · 7 across the 4 of their papers we have counts for

collaborators

5 papers

cs.AI20221 cited

ON-DEMAND-FL: A Dynamic and Efficient Multi-Criteria Federated Learning Client Deployment Scheme

Mario Chahoud, Hani Sami, Azzam Mourad +4

In this paper, we increase the availability and integration of devices in the learning process to enhance the convergence of federated learning (FL) models. To address the issue of…

cs.LG2022

FedMint: Intelligent Bilateral Client Selection in Federated Learning with Newcomer IoT Devices

Osama Wehbi, Sarhad Arisdakessian, Omar Abdel Wahab +4

Federated Learning (FL) is a novel distributed privacy-preserving learning paradigm, which enables the collaboration among several participants (e.g., Internet of Things devices) f…

eess.IV20224 cited

A Federated Learning Scheme for Neuro-developmental Disorders: Multi-Aspect ASD Detection

Hala Shamseddine, Safa Otoum, Azzam Mourad

Autism Spectrum Disorder (ASD) is a neuro-developmental syndrome resulting from alterations in the embryological brain before birth. This disorder distinguishes its patients by spe…

cs.DC20212 cited

DHT-based Communications Survey: Architectures and Use Cases

Yahya Hassanzadeh-Nazarabadi, Sanaz Taheri-Boshrooyeh, Safa Otoum +2

Several distributed system paradigms utilize Distributed Hash Tables (DHTs) to realize structured peer-to-peer (P2P) overlays. DHT structures arise as the most commonly used organi…

cs.CR2021

Preventing and Controlling Epidemics through Blockchain-Assisted AI-Enabled Networks

Safa Otoum, Ismaeel Al Ridhawi, Hussein T. Mouftah

The COVID-19 pandemic, which spread rapidly in late 2019, has revealed that the use of computing and communication technologies provides significant aid in preventing, controlling,…