PrivFL: Practical Privacy-preserving Federated Regressions on High-dimensional Data over Mobile Networks

Proceedings of the 2019 ACM SIGSAC Conference on Cloud Computing Security Workshop, pp. 57-68, 2019.

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Keywords:
federated learning machine learning predictive analysis privacy-preserving computation

Abstract:

Federated Learning (FL) enables a large number of users to jointly learn a shared machine learning (ML) model, coordinated by a centralized server, where the data is distributed across multiple devices. This approach enables the server or users to train and learn an ML model using gradient descent, while keeping all the training data on u...More

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