clustered federated learning 1distributed expectation-maximization 1federated learning 1metadata clustering 1privacy-preserving learning 1
From the 1 of 3 linked papers with an AI index.
3 papers
cs.LG2026
Encryption-Compatible Clustered Federated Learning via Distributed Expectation-Maximization over Metadata
Michael Ben Ali, Imen Megdiche, André Péninou +1
The paper introduces FLAMECHE, a method that reformulates metadata‑based clustered federated learning as a distributed Expectation‑Maximization process, allowing additive server up…
stat.ML2026
A survey on Clustered Federated Learning: Taxonomy, Analysis and Applications
Michael Ben Ali, Omar El-Rifai, Imen Megdiche +2
As Federated Learning (FL) expands, the challenge of non-independent and identically distributed (non-IID) data becomes critical. Clustered Federated Learning (CFL) addresses this…
cs.LG2025
A Robust Clustered Federated Learning Approach for Non-IID Data with Quantity Skew
Michael Ben Ali, Imen Megdiche, André Peninou +1
Federated Learning (FL) is a decentralized paradigm that enables a client-server architecture to collaboratively train a global Artificial Intelligence model without sharing raw da…