Federated Neural Collaborative Filtering. (arXiv:2106.04405v2 [cs.IR] UPDATED)

In this work, we present a federated version of the state-of-the-art Neural
Collaborative Filtering (NCF) approach for item recommendations. The system,
named FedNCF, enables learning without requiring users to disclose or transmit
their raw data. Data localization preserves data privacy and complies with
regulations such as the GDPR. Although federated learning enables model
training without local data dissemination, the transmission of raw clients'
updates raises additional privacy issues. To address this challenge, we
incorporate a privacy-preserving aggregation method that satisfies …

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