Modulated learning for private and distributed regression with just a single sample per client device

Praneeth Vepakomma, Amirhossein Reisizadeh, Samuel Horváth +1

This work focuses on the question of learning from a large number of devices with each device holding only a single sample of data. Several real-world applications exist to this on…