4 papers
Dropout-Robust Mechanisms for Differentially Private and Fully Decentralized Mean Estimation
César Sabater, Sonia Ben Mokhtar, Jan Ramon
Achieving differentially private computations in decentralized settings poses significant challenges, particularly regarding accuracy, communication cost, and robustness against in…
Secure Federated Graph-Filtering for Recommender Systems
Julien Nicolas, César Sabater, Mohamed Maouche +2
Recommender systems often rely on graph-based filters, such as normalized item-item adjacency matrices and low-pass filters. While effective, the centralized computation of these c…
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…
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…