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cs.LG2025
Exposing the Vulnerability of Decentralized Learning to Membership Inference Attacks Through the Lens of Graph Mixing
Ousmane Touat, Jezekael Brunon, Yacine Belal +4
The primary promise of decentralized learning is to allow users to engage in the training of machine learning models in a collaborative manner while keeping their data on their pre…
cs.LG2025
Differentially private and decentralized randomized power method
Julien Nicolas, César Sabater, Mohamed Maouche +2
The randomized power method has gained significant interest due to its simplicity and efficient handling of large-scale spectral analysis and recommendation tasks. However, its app…