Mohamed Adel Attia

Information Theoretic Limits of Data Shuffling for Distributed Learning

2016

Data shuffling is one of the fundamental building blocks for distributed learning algorithms, that increases the statistical gain for each step of the learning process. In each iteration, different shuffled data points are assigned by …