74 citations · 89 across the 8 of their papers we have counts for
8 papers
Optimized Federated Knowledge Distillation with Distributed Neural Architecture Search
Chaimaa Medjadji, Sylvain Kubler, Yves Le Traon +3
Federated Learning (FL) enables collaborative model training without centralizing data. However, real-world deployments must simultaneously address statistical heterogeneity across…
FedSparQ: Adaptive Sparse Quantization with Error Feedback for Robust & Efficient Federated Learning
Chaimaa Medjadji, Sadi Alawadi, Feras M. Awaysheh +3
Federated Learning (FL) enables collaborative model training across decentralized clients while preserving data privacy by keeping raw data local. However, FL suffers from signific…
Edge AI in Highly Volatile Environments: Is Fairness Worth the Accuracy Trade-off?
Obaidullah Zaland, Feras M. Awaysheh, Sawsan Al Zubi +2
Federated learning (FL) has emerged as a transformative paradigm for edge intelligence, enabling collaborative model training while preserving data privacy across distributed perso…
Quantum Computing as a Service -- a Software Engineering Perspective
Aakash Ahmad, Muhammad Waseem, Bakheet Aljedaani +3
Quantum systems have started to emerge as a disruptive technology and enabling platforms - exploiting the principles of quantum mechanics via programmable quantum bits (QuBits) - t…
Next Generation Cloud-native In-Memory Stores: From Redis to Valkey and Beyond
Carl-Johan Fauvelle Munck af Rosensch"old, Feras M. Awaysheh, Ahmad Awad
In-memory key-value datastores have become indispensable building blocks of modern cloud-native infrastructures, yet their evolution faces scalability, compatibility, and sustainab…
BEST: A Unified Business Process Enactment via Streams and Tables for Service Computing
Ahmed Awad, Feras Awaysheh, Hugo A. López
Business process models are essential for the representation, analysis, and execution of organizational processes, serving as orchestration blueprints while relying on (web) servic…
FedCSD: A Federated Learning Based Approach for Code-Smell Detection
Sadi Alawadi, Khalid Alkharabsheh, Fahed Alkhabbas +4
This paper proposes a Federated Learning Code Smell Detection (FedCSD) approach that allows organizations to collaboratively train federated ML models while preserving their data p…
Next-Generation Big Data Federation Access Control: A Reference Model
Feras M. Awaysheh, Mamoun Alazab, Maanak Gupta +2
This paper discusses one of the most significant challenges of next-generation big data (BD) federation platforms, namely, Hadoop access control. Privacy and security on a federati…