Solving machine learning optimization problems using quantum computers

2019/11/17 by Venkat R. Dasari, Dasari, Venkat R., Mee Seong Im +3
Computer Science · Mathematics · Physics and Astronomy · #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Quantum Physics (quant-ph) #cs.LG #quant-ph #stat.ML

paper · pdf · doi:10.48550/arxiv.1911.08587

5 pages, 3 figures. Submitted to Proc. SPIE

arxiv created 2019/11/17 · arxiv updated 2019/11/21

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 3-dimensional image that vary with time.

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