Quantum Optimized Centroid Initialization
Quantum Physics
2023-05-16 v1 Emerging Technologies
Abstract
One of the major benefits of quantum computing is the potential to resolve complex computational problems faster than can be done by classical methods. There are many prototype-based clustering methods in use today, and the selection of the starting nodes for the center points is often done randomly. Clustering often suffers from accepting a local minima as a valid solution when there are possibly better solutions. We will present the results of a study to leverage the benefits of quantum computing for finding better starting centroids for prototype-based clustering.
Cite
@article{arxiv.2305.08626,
title = {Quantum Optimized Centroid Initialization},
author = {Nicholas R. Allgood and Ajinkya Borle and Charles K. Nicholas},
journal= {arXiv preprint arXiv:2305.08626},
year = {2023}
}