4 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…
Federated Imputation under Heterogeneous Feature Spaces
Imane Hocine, Chaimaa Medjadji, Sylvain Kubler +2
Federated Learning (FL) enables collaborative training across decentralized clients, but most methods assume aligned feature schemas, an assumption that rarely holds in tabular set…
Centralized vs Decentralized Federated Learning: A trade-off performance analysis
Chaimaa Medjadji, Guilain Leduc, Sylvain Kubler +1
Federated Learning (FL) has emerged as a promising paradigm for collaborative model training across distributed edge devices while preserving data privacy especially with the huge…
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…