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"Privacy-Preserving federated learning in medical diagnosis with homomo" by Hanchao Ku, Willy Susilo et al.

Unlike traditional centralized machine learning, distributed machine learning provides more efficient and useful application scenarios. However, distributed learning may not meet some security requirements. For example, in medical treatment and diagnosis, an increasing number of people are using IoT devices to record their personal data, when training medical data, the users are not willing to reveal their private data to the training party. How to collect and train the data securely has become ...
Federated Learning Gradient Descent Omomorphic Re Encryption Privacy Preserving
Source: uow.edu.au

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