IEICE TRANSACTIONS on Information
Quantum Algorithm on Logistic Regression Problem
Summary :
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.
- Publication
- IEICE TRANSACTIONS on Information 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
Authors
Jun Suk KIM
Gwangju Institute of Science and Technology
Chang Wook AHN
Gwangju Institute of Science and Technology
Keyword
Latest Issue
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Jun Suk KIM, Chang Wook AHN, "Quantum Algorithm on Logistic Regression Problem" in IEICE TRANSACTIONS on Information,
vol. E102-D, no. 4, pp. 856-858, April 2019, doi: 10.1587/transinf.2018EDL8223.
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.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2018EDL8223/_p
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@ARTICLE{e102-d_4_856,
author={Jun Suk KIM, Chang Wook AHN, },
journal={IEICE TRANSACTIONS on Information},
title={Quantum Algorithm on Logistic Regression Problem},
year={2019},
volume={E102-D},
number={4},
pages={856-858},
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.},
keywords={},
doi={10.1587/transinf.2018EDL8223},
ISSN={1745-1361},
month={April},}
Copy
TY - JOUR
TI - Quantum Algorithm on Logistic Regression Problem
T2 - IEICE TRANSACTIONS on Information
SP - 856
EP - 858
AU - Jun Suk KIM
AU - Chang Wook AHN
PY - 2019
DO - 10.1587/transinf.2018EDL8223
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E102-D
IS - 4
JA - IEICE TRANSACTIONS on Information
Y1 - April 2019
AB - 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.
ER -
English
