Author Archives: Aishwarya Srinivasan

25 Jan

Council Post: Overcoming the cyclical challenge of data utility and data privacy through Federated Learning

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One of the defining characterist wwwics of federated learning is that it keeps raw data decentralised, train model decentralised and then aggregate. Unlike traditional data centre-based distributed learning settings where data is arbitrarily distributed and any node within the network can access the data, Federated Learning involves heterogeneous distributed data to help protect privacy.