A Decentralized Federated Learning using Reputation

ePrint Report: A Decentralized Federated Learning using Reputation

Olive Chakraborty, Aymen Boudguiga

Nowadays Federated learning (FL) is established as one of the best techniques for collaborative machine learning. It allows a set of clients to train a common model without disclosing their sensitive and private
dataset to a coordination server. The latter is in charge of the model aggregation. However, FL faces some problems, regarding the security of updates, integrity of computation and the availability of a server.
In this …

clients coordination dataset decentralized eprint report federated federated learning machine machine learning private report reputation sensitive server techniques train