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.
Are Quantum Classifiers Promising? / Tamburini F.. - ELETTRONICO. - 1:1(2014), pp. 360-364. (Intervento presentato al convegno The First Italian Conference on Computational Linguistics CLiC-it 2014 tenutosi a Pisa nel 9-10 dicembre 2014).
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.File in questo prodotto:
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