Paper Abstract and Keywords |
Presentation |
2017-11-09 13:00
Quantum inspired Machine Learning through Entanglement Entropy Masaru Tanaka (Fukuoka UNiv.) IBISML2017-50 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
CNN has been successful in image classification, but we want to focus on the relationship with other fields. In particular, given an input image, each pixel in the image is often assumed to be independent, but it is considered as a kind of wave function to bring a kind of correlation between each pixel. In this report, the background considering this is discussed in detail. In particular, it is necessary to consider the partial system in situations where information of all systems cannot be completely obtained for some reason, but this is shown to lead to the concept of entropy entropy. It is also possible to consider the probability distribution according to the power law as a means to catch the partial system. The reason for this is also shown in concrete terms. Among these techniques, Egguchee will give some specific application of the entangement entropy to partial systems (IBIS 2017). |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
subsystem / entanglement entropy / power law / convolutional neural network / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 117, no. 293, IBISML2017-50, pp. 115-122, Nov. 2017. |
Paper # |
IBISML2017-50 |
Date of Issue |
2017-11-02 (IBISML) |
ISSN |
Print edition: ISSN 0913-5685 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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IBISML2017-50 |
Conference Information |
Committee |
IBISML |
Conference Date |
2017-11-08 - 2017-11-10 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Univ. of Tokyo |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Information-Based Induction Science Workshop (IBIS2017) |
Paper Information |
Registration To |
IBISML |
Conference Code |
2017-11-IBISML |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Quantum inspired Machine Learning through Entanglement Entropy |
Sub Title (in English) |
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subsystem |
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entanglement entropy |
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power law |
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convolutional neural network |
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1st Author's Name |
Masaru Tanaka |
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Fukuoka UNIversity (Fukuoka UNiv.) |
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Speaker |
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Date Time |
2017-11-09 13:00:00 |
Presentation Time |
150 minutes |
Registration for |
IBISML |
Paper # |
IBISML2017-50 |
Volume (vol) |
vol.117 |
Number (no) |
no.293 |
Page |
pp.115-122 |
#Pages |
8 |
Date of Issue |
2017-11-02 (IBISML) |
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