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Found 2 papers, 1 papers with code
Federated Multi-view Matrix Factorization for Personalized Recommendations
We introduce the federated multi-view matrix factorization method that extends the federated learning framework to matrix factorization with multiple data sources.
Federated Collaborative Filtering for Privacy-Preserving Personalized Recommendation System
In the Federated Learning paradigm, a master machine learning model is distributed to user clients, the clients use their locally stored data and model for both inference and calculating model updates.
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