Model Segmentation for Storage Efficient Private Federated Learning with Top $r$ Sparsification. (arXiv:2212.11947v1 [cs.IT])

In federated learning (FL) with top $r$ sparsification, millions of users
collectively train a machine learning (ML) model locally, using their personal
data by only communicating the most significant $r$ fraction of updates to
reduce the communication cost. It has been shown that the values as well as the
indices of these selected (sparse) updates leak information about the users'
personal data. In this work, we investigate different methods to carry out
user-database communications in FL with top $r$ sparsification …

federated learning segmentation storage