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.
(2023). Local Approach to Quantum-inspired Classification [journal article - articolo]. In INTERNATIONAL JOURNAL OF THEORETICAL PHYSICS. Retrieved from https://hdl.handle.net/10446/234049
Local Approach to Quantum-inspired Classification
Leporini, Roberto;
2023-01-01
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.File allegato/i alla scheda:
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