Learning quantum data with the quantum earth mover’s distance

Quantifying how far the output of a learning algorithm is from its target is an essential task in machine learning. However, in quantum settings, the loss landscapes of commonly used distance metrics often produce undesirable outcomes such as poor local minima and exponentially decaying gradients. T...

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Bibliographic Details
Main Authors: Kiani, Bobak Toussi, De Palma, Giacomo, Marvian, Milad, Liu, Zi-Wen, Lloyd, Seth
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Format: Article
Language:English
Published: IOP Publishing 2024
Subjects:
Online Access:https://hdl.handle.net/1721.1/153938