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| Presentation | 2019-03-14 15:35 Effect of Dropout Layers of Neural Networks Applied for Iterative Error-Detection Clustering Method Taishi Watanabe, Masayuki Yamauchi (Hiroshima Institute of Tech.), Mamoru Tanaka (Sophia Univ.)  NLP2018-130 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | IoT has been continued to develop greatly. It is important that cluttered big data need to be used effectively on internet. Clustering is one of important techniques for seperating and analyzing of big data. There is a ``Iterative Error-detection type clustering method system'' with Neural Networks that we have developed. We investigate the effect of the Dropout layer which is thought to device considered useful for optimization of the system. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Clustering / Iterative Error-Detection / Neural Networks / Classification / Data Mining / Dropout / / | |
| Reference Info. | IEICE Tech. Rep., vol. 118, no. 498, NLP2018-130, pp. 31-36, March 2019. | |
| Paper # | NLP2018-130 | |
| Date of Issue | 2019-03-07 (NLP) | |
| 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) | |
| Download PDF | NLP2018-130 |
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| Conference Information | |
| Committee | NLP MSS |
| Conference Date | 2019-03-14 - 2019-03-15 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Bunkyo Camp., Univ. of Fukui |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | SICE-DES, IEICE-MSS, IEICE-NLP, Work In Progress, and etc. |
| Paper Information | |
| Registration To | NLP |
| Conference Code | 2019-03-NLP-MSS |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Effect of Dropout Layers of Neural Networks Applied for Iterative Error-Detection Clustering Method |
| Sub Title (in English) | |
| Keyword(1) | Clustering |
| Keyword(2) | Iterative Error-Detection |
| Keyword(3) | Neural Networks |
| Keyword(4) | Classification |
| Keyword(5) | Data Mining |
| Keyword(6) | Dropout |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Taishi Watanabe |
| 1st Author's Affiliation | Hiroshima Institute of Technology (Hiroshima Institute of Tech.) |
| 2nd Author's Name | Masayuki Yamauchi |
| 2nd Author's Affiliation | Hiroshima Institute of Technology (Hiroshima Institute of Tech.) |
| 3rd Author's Name | Mamoru Tanaka |
| 3rd Author's Affiliation | Sophia University (Sophia Univ.) |
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| Speaker | Author-1 |
| Date Time | 2019-03-14 15:35:00 |
| Presentation Time | 25 minutes |
| Registration for | NLP |
| Paper # | NLP2018-130 |
| Volume (vol) | vol.118 |
| Number (no) | no.498 |
| Page | pp.31-36 |
| #Pages | 6 |
| Date of Issue | 2019-03-07 (NLP) |
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