Federated Quantum Natural Gradient Descent for Quantum Federated Learning. (arXiv:2209.00564v1 [quant-ph])

The heart of Quantum Federated Learning (QFL) is associated with a
distributed learning architecture across several local quantum devices and a
more efficient training algorithm for the QFL is expected to minimize the
communication overhead among different quantum participants. In this work, we
put forth an efficient learning algorithm, namely federated quantum natural
gradient descent (FQNGD), applied in a QFL framework which consists of the
variational quantum circuit (VQC)-based quantum neural networks (QNN). The
FQNGD algorithm admits much fewer training …

arxiv federated learning gradient learning natural quantum