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Título
A review of k-NN algorithm based on classical and Quantum Machine Learning
Autor(es)
Materia
Machine learning
Supervised learning
k-Nearest Neighbors
Quantum computing
Quantum k-NN
Clasificación UNESCO
5306.02 Innovación Tecnológica
1203.04 Inteligencia Artificial
Fecha de publicación
2020
Editor
SpringerLink
Citación
Mezquita, Y., et al. (2020). A Review of k-NN Algorithm Based on Classical and Quantum Machine. Learning.Advances in Intelligent Systems and Computing, vol 1242. Springer, Cham.
Serie / N.º
AISC;1242
Resumen
[EN] Artificial intelligence algorithms, developed for traditional computing, based on Von Neumann’s architecture, are slow and expensive in terms of computational resources. Quantum mechanics has opened
up a new world of possibilities within this field, since, thanks to the basic
properties of a quantum computer, a great degree of parallelism can be
achieved in the execution of the quantum version of machine learning
algorithms. In this paper, a study has been carried out on these proper-
ties and on the design of their quantum computing versions. More specif-
ically, the study has been focused on the quantum version of the k-NN
algorithm that allows to understand the fundamentals when transcribing
classical machine learning algorithms into its quantum versions.
URI
ISBN
978-3-030-53828-6
DOI
10.1007/978-3-030-53829-3_20
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