This paper presents work in progress on the development of a new gen- eral purpose classifier based on Quantum Probability Theory. We will propose a kernel-based formulation of this classifier that is able to compete with a state-of-the- art machine learning methods when clas- sifying instances from two hard artificial problems and two real tasks taken from the speech processing domain.

Tamburini, F. (2014). Are Quantum Classifiers Promising?. Pisa : Pisa University Press.

Are Quantum Classifiers Promising?

TAMBURINI, FABIO
2014

Abstract

This paper presents work in progress on the development of a new gen- eral purpose classifier based on Quantum Probability Theory. We will propose a kernel-based formulation of this classifier that is able to compete with a state-of-the- art machine learning methods when clas- sifying instances from two hard artificial problems and two real tasks taken from the speech processing domain.
2014
The First Italian Conference on Computational Linguistics CLiC-it 2014. Proceedings
360
364
Tamburini, F. (2014). Are Quantum Classifiers Promising?. Pisa : Pisa University Press.
Tamburini, Fabio
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/479977
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