Adaptive Verifiable Coded Computing: Towards Fast, Secure and Private Distributed Machine Learning. (arXiv:2107.12958v2 [cs.DC] UPDATED)

Stragglers, Byzantine workers, and data privacy are the main bottlenecks in
distributed cloud computing. Some prior works proposed coded computing
strategies to jointly address all three challenges. They require either a large
number of workers, a significant communication cost or a significant
computational complexity to tolerate Byzantine workers. Much of the overhead in
prior schemes comes from the fact that they tightly couple coding for all three
problems into a single framework. In this paper, we propose Adaptive Verifiable
Coded …

computing dc distributed fast machine machine learning