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Hofman, Stefan (author)
An increase in the performance of mobile devices has started a revolution in deploying artificial intelligence (AI) algorithms on mobile and embedded systems. In addition, fueled by the need for privacy-aware insights into data, we see a strong push towards federated machine learning, where data is stored locally and not shared with a central...
master thesis 2020
Enthoven, David (author)
With the increasing number of data collectors such as smartphones, immense amounts of data are available. These data have great value for training machine learning models. Federated learning is a distributed machine learning approach that allows a machine learning model to train on a distributed data-set without transferring any data and...
master thesis 2019