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arXiv · 2305.08626

Quantum Optimized Centroid Initialization

Nicholas R. Allgood·Ajinkya Borle·Charles K. Nicholas
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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.

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Nicholas R. Allgood, Ajinkya Borle, Charles K. Nicholas. 2023-05-15. Quantum Optimized Centroid Initialization. https://arxiv.org/abs/2305.08626

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