Quantum Interference for Counting Clusters
Machine Learning
2020-01-14 v1 Quantum Physics
Machine Learning
Abstract
Counting the number of clusters, when these clusters overlap significantly is a challenging problem in machine learning. We argue that a purely mathematical quantum theory, formulated using the path integral technique, when applied to non-physics modeling leads to non-physics quantum theories that are statistical in nature. We show that a quantum theory can be a more robust statistical theory to separate data to count overlapping clusters. The theory is also confirmed from data simulations.This works identify how quantum theory can be effective in counting clusters and hope to inspire the field to further apply such techniques.
Cite
@article{arxiv.2001.04251,
title = {Quantum Interference for Counting Clusters},
author = {Rohit R Muthyala and Davi Geiger and Zvi M. Kedem},
journal= {arXiv preprint arXiv:2001.04251},
year = {2020}
}