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A Federated Multi-View Deep Learning Framework for Privacy-Preserving Recommendations
[article]
2020
arXiv
pre-print
Privacy-preserving recommendations are recently gaining momentum, since the decentralized user data is increasingly harder to collect, by recommendation service providers, due to the serious concerns over user privacy and data security. This situation is further exacerbated by the strict government regulations such as Europe's General Data Privacy Regulations(GDPR). Federated Learning(FL) is a newly developed privacy-preserving machine learning paradigm to bridge data repositories without
arXiv:2008.10808v1
fatcat:nxsmztc4grdadj3ayzvmsb3xiq