Quantum Algorithm on Logistic Regression Problem

Jun Suk KIM  Chang Wook AHN  

IEICE TRANSACTIONS on Information and Systems   Vol.E102-D   No.4   pp.856-858
Publication Date: 2019/04/01
Publicized: 2019/01/28
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2018EDL8223
Type of Manuscript: LETTER
Category: Fundamentals of Information Systems
quantum machine learning,  Deutsch-Jozsa Algorithm,  logistic regression,  feature selection,  

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We examine the feasibility of Deutsch-Jozsa Algorithm, a basic quantum algorithm, on a machine learning-based logistic regression problem. Its major property to distinguish the function type with an exponential speedup can help identify the feature unsuitability much more quickly. Although strict conditions and restrictions to abide exist, we reconfirm the quantum superiority in many aspects of modern computing.