Paper Abstract and Keywords |
Presentation |
2023-03-14 15:45
Improvement of the Performance for Quantum Neural Network Classifiers based on Optimal Quantum Measurement Decoding Yusaku Yamada, Jun Suzuki (UEC) IT2022-106 ISEC2022-85 WBS2022-103 RCC2022-103 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In this work, we study the problem of supervised label classification using quantum neural network (QNN). We propose a method of optimal quantum measurement decoding (OQMD) that optimizes single qubit measurements before decoding classical data from quantum states. We apply OQMD to the Iris Data Set to illustrate effectiveness of our proposal. OQMD achieves the accuracy of 95% classification even for relatively simple quantum circuits, which are regarded as useless in previous works. Comparison with the previous proposals based on heuristic approaches, we argue that the more fundamental is to perform optimal measurement to decode classical data in the QNN classification problem. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Quantum Computing / Quantum Neural Networks / Quantum Machine Learning / Parameterized Quantum Circuits / Variational Quantum Circuits / FeatureMap / Optimal Measurements / |
Reference Info. |
IEICE Tech. Rep., vol. 122, no. 427, IT2022-106, pp. 242-247, March 2023. |
Paper # |
IT2022-106 |
Date of Issue |
2023-03-07 (IT, ISEC, WBS, RCC) |
ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
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IT2022-106 ISEC2022-85 WBS2022-103 RCC2022-103 |
Conference Information |
Committee |
RCC ISEC IT WBS |
Conference Date |
2023-03-14 - 2023-03-15 |
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(See Japanese page) |
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Paper Information |
Registration To |
IT |
Conference Code |
2023-03-RCC-ISEC-IT-WBS |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Improvement of the Performance for Quantum Neural Network Classifiers based on Optimal Quantum Measurement Decoding |
Sub Title (in English) |
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Keyword(1) |
Quantum Computing |
Keyword(2) |
Quantum Neural Networks |
Keyword(3) |
Quantum Machine Learning |
Keyword(4) |
Parameterized Quantum Circuits |
Keyword(5) |
Variational Quantum Circuits |
Keyword(6) |
FeatureMap |
Keyword(7) |
Optimal Measurements |
Keyword(8) |
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1st Author's Name |
Yusaku Yamada |
1st Author's Affiliation |
The University of Electro-Communications (UEC) |
2nd Author's Name |
Jun Suzuki |
2nd Author's Affiliation |
The University of Electro-Communications (UEC) |
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Speaker |
Author-1 |
Date Time |
2023-03-14 15:45:00 |
Presentation Time |
25 minutes |
Registration for |
IT |
Paper # |
IT2022-106, ISEC2022-85, WBS2022-103, RCC2022-103 |
Volume (vol) |
vol.122 |
Number (no) |
no.427(IT), no.428(ISEC), no.429(WBS), no.430(RCC) |
Page |
pp.242-247 |
#Pages |
6 |
Date of Issue |
2023-03-07 (IT, ISEC, WBS, RCC) |
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