Year: 2023
Type: article
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.
Source: Entropy
DOI: 10.3390/e25030404
Authors: Cesarino Bertini, Roberto Leporini
Institution: University of Bergamo
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,224
OpenAlex ID: W4321601533