Dimension Reduction and Redundancy Removal through Successive Schmidt Decompositions

Quantum computers are believed to have the ability to process huge data sizes, which can be seen in machine learning applications. In these applications, the data, in general, are classical. Therefore, to process them on a quantum computer, there is a need for efficient methods that can be used to m...

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Bibliographic Details

Published in:	Applied Sciences
Main Authors:	Ammar Daskin, Rishabh Gupta, Sabre Kais
Format:	Article
Language:	English
Published:	MDPI AG 2023-03-01
Subjects:	quantum machine learning quantum algorithms tensor decomposition data mapping dimension reduction
Online Access:	https://www.mdpi.com/2076-3417/13/5/3172