Adiabatic Quantum Computing for Binary Clustering
Machine Learning
2017-06-20 v1 Quantum Physics
Abstract
Quantum computing for machine learning attracts increasing attention and recent technological developments suggest that especially adiabatic quantum computing may soon be of practical interest. In this paper, we therefore consider this paradigm and discuss how to adopt it to the problem of binary clustering. Numerical simulations demonstrate the feasibility of our approach and illustrate how systems of qubits adiabatically evolve towards a solution.
Cite
@article{arxiv.1706.05528,
title = {Adiabatic Quantum Computing for Binary Clustering},
author = {Christian Bauckhage and Eduardo Brito and Kostadin Cvejoski and Cesar Ojeda and Rafet Sifa and Stefan Wrobel},
journal= {arXiv preprint arXiv:1706.05528},
year = {2017}
}