7 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…
A Feature-Driven Framework for Software Fault Prediction
Ahmad Nauman Ghazi, Nagajyothi Devarapalli, Ashir Javeed +3
Software fault prediction (SFP) is a critical task in software engineering, enabling early identification of faults in modules to improve software quality and reduce maintenance co…
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…
From Requirements to Test Cases: An NLP-Based Approach for High-Performance ECU Test Case Automation
Nikitha Medeshetty, Ahmad Nauman Ghazi, Sadi Alawadi +1
Automating test case specification generation is vital for improving the efficiency and accuracy of software testing, particularly in complex systems like high-performance Electron…
SHEDAD: SNN-Enhanced District Heating Anomaly Detection for Urban Substations
Jonne van Dreven, Abbas Cheddad, Sadi Alawadi +3
District Heating (DH) systems are essential for energy-efficient urban heating. However, despite the advancements in automated fault detection and diagnosis (FDD), DH still faces c…
Toward efficient resource utilization at edge nodes in federated learning
Sadi Alawadi, Addi Ait-Mlouk, Salman Toor +1
Federated learning (FL) enables edge nodes to collaboratively contribute to constructing a global model without sharing their data. This is accomplished by devices computing local,…