3 papers
cs.NI2026
FLAIR: Distributed Federated Learning with Dynamic Clustering
Ihssan Boutebicha, Bilel Zaghdoudi, Mohamed Amine Legheraba +1
Federated Learning (FL) offers a privacy-preserving framework for distributed machine learning, yet conventional centralized and hierarchical architectures present significant chal…
cs.LG2026
HEAL: Resilient and Self-* Hub-based Learning
Mohamed Amine Legheraba, Stefan Galkiewicz, Maria Gradinariu Potop-Butucaru +1
Decentralized learning enhances privacy, scalability, and fault tolerance by distributing data and computation across nodes. A popular approach is Federated learning, which relies…
cs.DS2024
Distributed computation of temporal twins in periodic undirected time-varying graphs
Lina Azerouk, Binh-Minh Bui-Xuan, Camille Palisoc +2
Twin nodes in a static network capture the idea of being substitutes for each other for maintaining paths of the same length anywhere in the network. In dynamic networks, we model…