Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification

13 Sep 2019Tzu-Ming Harry HsuHang QiMatthew Brown

Federated Learning enables visual models to be trained in a privacy-preserving way using real-world data from mobile devices. Given their distributed nature, the statistics of the data across these devices is likely to differ significantly... (read more)

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