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cs.LG2021★ 1 cited
Fidel: Reconstructing Private Training Samples from Weight Updates in Federated Learning
David Enthoven, Zaid Al-Ars
With the increasing number of data collectors such as smartphones, immense amounts of data are available. Federated learning was developed to allow for distributed learning on a ma…
cs.LG2020
Privacy-Preserving Object Detection & Localization Using Distributed Machine Learning: A Case Study of Infant Eyeblink Conditioning
Stefan Zwaard, Henk-Jan Boele, Hani Alers +3
Distributed machine learning is becoming a popular model-training method due to privacy, computational scalability, and bandwidth capacities. In this work, we explore scalable dist…