Local Approach to Quantum-inspired Classification

被引：0

作者：

Enrico Blanzieri

Roberto Leporini

Davide Pastorello

机构：

[1] University of Trento,Department of Information Engineering and Computer Science

[2] TIFPA-INFN,Department of Economics

[3] University of Bergamo,undefined

来源：

International Journal of Theoretical Physics | / 62卷

关键词：

Quantum state discrimination; k-nearest neighbors; Machine learning;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

In the context of quantum-inspired machine learning, remarkable mathematical tools for solving classification problems are given by some methods of quantum state discrimination. In this respect, quantum-inspired classifiers based on nearest centroid and Helstrom discrimination have been efficiently implemented on classical computers. We present a local approach combining the kNN algorithm to some quantum-inspired classifiers.

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