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Quantum-Inspired Applications for Classification Problems
Cesarino Bertini1, Roberto Leporini2
1Department of Management, University of Bergamo, via dei Caniana 2, I-24127 Bergamo, Italy.
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.
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