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Quantum Algorithm on Logistic Regression Problem

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Author(s)
Kim, Jun SukAhn, Chang Wook
Type
Article
Citation
Ieice Transactions on Information and Systems, v.E102D, no.4, pp.856 - 858
Issued Date
2019-04
Abstract
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.
Publisher
IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG
ISSN
1745-1361
DOI
10.1587/transinf.2018EDL8223
URI
https://scholar.gist.ac.kr/handle/local/12762
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