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An efficient quantum algorithm for ensemble classification using bagging

Abstract Ensemble methods aggregate predictions from multiple models, typically demonstrating improved accuracy and reduced variance compared to individual classifiers. However, they often come with significant memory usage and computational time requirements. A novel quantum algorithm that leverage...

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Hauptverfasser: Antonio Macaluso, Luca Clissa, Stefano Lodi, Claudio Sartori
Format: Artigo
Sprache:Inglês
Veröffentlicht: Wiley 2024-09-01
Schriftenreihe:IET Quantum Communication
Schlagworte:
Online-Zugang:https://doi.org/10.1049/qtc2.12087
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