Solving machine learning optimization problems using quantum computers
Quantum Physics
2019-11-21 v1 Machine Learning
Machine Learning
Abstract
Classical optimization algorithms in machine learning often take a long time to compute when applied to a multi-dimensional problem and require a huge amount of CPU and GPU resource. Quantum parallelism has a potential to speed up machine learning algorithms. We describe a generic mathematical model to leverage quantum parallelism to speed-up machine learning algorithms. We also apply quantum machine learning and quantum parallelism applied to a -dimensional image that vary with time.
Cite
@article{arxiv.1911.08587,
title = {Solving machine learning optimization problems using quantum computers},
author = {Venkat R. Dasari and Mee Seong Im and Lubjana Beshaj},
journal= {arXiv preprint arXiv:1911.08587},
year = {2019}
}
Comments
5 pages, 3 figures. Submitted to Proc. SPIE