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.

Local Approach to Quantum-inspired Classification / Enrico Blanzieri; Roberto Leporini; Davide Pastorello. - In: INTERNATIONAL JOURNAL OF THEORETICAL PHYSICS. - ISSN 0020-7748. - ELETTRONICO. - 62:1(2022), pp. 4.1-4.10. [10.1007/s10773-022-05263-y]

Local Approach to Quantum-inspired Classification

Davide Pastorello
2022

Abstract

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.
2022
Local Approach to Quantum-inspired Classification / Enrico Blanzieri; Roberto Leporini; Davide Pastorello. - In: INTERNATIONAL JOURNAL OF THEORETICAL PHYSICS. - ISSN 0020-7748. - ELETTRONICO. - 62:1(2022), pp. 4.1-4.10. [10.1007/s10773-022-05263-y]
Enrico Blanzieri; Roberto Leporini; Davide Pastorello
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/926048
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