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Federated Learning
Atelier aux Transnumériques 2026 : Résilience et confidentialité de l’IA et de l’IA distribuée
Un regard croisé entre les projets IPoP, SSF-ML-DH et REDEEM sur l’IA de confiance.
Cédric Gouy-Pailler
,
Sonia Ben Mokhtar
Feb 3, 2026
2 min read
Events
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AI
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Cybersecurity
Adaptive Collaboration for Online Personalized Distributed Learning with Heterogeneous Clients
We study the problem of online personalized decentralized learning with NNN statistically heterogeneous clients collaborating to …
Constantin Philippenko
,
Batiste Le Bars
,
Kevin Scaman
,
Laurent Massoulie
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Federated Majorize-Minimization: Beyond Parameter Aggregation
This paper proposes a unified approach for designing stochastic optimization algorithms that robustly scale to the federated learning …
Aymeric Dieuleveut
,
Gersende Fort
,
Mahmoud Hegazy
,
Hoi-to Wai
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In-Depth Analysis of Low-rank Matrix Factorisation in a Federated Setting
We analyze a distributed algorithm to compute a low-rank matrix factorization on NNN clients, each holding a local dataset …
Constantin Philippenko
,
Kevin Scaman
,
Laurent Massoulié
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