In the context of quantum-inspired machine learning, quantum state discrimination is a useful tool for classification problems. We implement a local approach combining the k-nearest neighbors algorithm with some quantum-inspired classifiers. We compare the performance with respect to well-known classifiers applied to benchmark datasets.

(2023). Quantum-Inspired Applications for Classification Problems [journal article - articolo]. In ENTROPY. Retrieved from https://hdl.handle.net/10446/239450

Quantum-Inspired Applications for Classification Problems

Bertini, Cesarino;Leporini, Roberto
2023-01-01

Abstract

In the context of quantum-inspired machine learning, quantum state discrimination is a useful tool for classification problems. We implement a local approach combining the k-nearest neighbors algorithm with some quantum-inspired classifiers. We compare the performance with respect to well-known classifiers applied to benchmark datasets.
articolo
2023
Bertini, Cesarino; Leporini, Roberto
(2023). Quantum-Inspired Applications for Classification Problems [journal article - articolo]. In ENTROPY. Retrieved from https://hdl.handle.net/10446/239450
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10446/239450
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