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| Presentation | 2012-11-17 13:30 Composite likelihood estimation for bipartite Boltzmann machines Takashi Asari, Muneki Yasuda, Yuji Waizumi, Kazuyuki Tanaka (Tohoku Univ.)  NC2012-68 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | The recent development of information technology has enabled us to obtain and to storage huge information data. Because of this, effective usages of the information data have been one of the central points of information sciences. A Boltzmann machine is a model of the machine learning theory and can be a powerful tool for the aim. In this paper, we focus on a bipartite Boltzmann machine (BBM) consisted of two different layers: one layer is the input layer and the other is the output layer. In this model, once the input layer is clamped by given data, inference of the output layer is quite easy because of the property of conditional independence. Therefore, this model is expected to be applied to expert systems such as medical test system. However, the learning of BBM using the maximum likelihood estimation is still intractable, Because the computational complexity of learning exponentially grows with the increase in the size of system, In this paper, we propose a new learning algorithm for BBM by using the composite likelihood estimation (CLE) which is a statistical mathematical technique to approximate the MLE. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | probabilistic information processing / statistical machine learning theory / Boltzmann machine / maximum likelihood estimation / composite likelihood estimation / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 112, no. 298, NC2012-68, pp. 39-44, Nov. 2012. | |
| Paper # | NC2012-68 | |
| Date of Issue | 2012-11-09 (NC) | |
| 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 | NC2012-68 |
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| Conference Information | |
| Committee | MBE NC |
| Conference Date | 2012-11-16 - 2012-11-17 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Tohoku University |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | BCI/BMI, NC and MBE |
| Paper Information | |
| Registration To | NC |
| Conference Code | 2012-11-MBE-NC |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Composite likelihood estimation for bipartite Boltzmann machines |
| Sub Title (in English) | |
| Keyword(1) | probabilistic information processing |
| Keyword(2) | statistical machine learning theory |
| Keyword(3) | Boltzmann machine |
| Keyword(4) | maximum likelihood estimation |
| Keyword(5) | composite likelihood estimation |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Takashi Asari |
| 1st Author's Affiliation | Tohoku University (Tohoku Univ.) |
| 2nd Author's Name | Muneki Yasuda |
| 2nd Author's Affiliation | Tohoku University (Tohoku Univ.) |
| 3rd Author's Name | Yuji Waizumi |
| 3rd Author's Affiliation | Tohoku University (Tohoku Univ.) |
| 4th Author's Name | Kazuyuki Tanaka |
| 4th Author's Affiliation | Tohoku University (Tohoku Univ.) |
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| Speaker | Author-1 |
| Date Time | 2012-11-17 13:30:00 |
| Presentation Time | 25 minutes |
| Registration for | NC |
| Paper # | NC2012-68 |
| Volume (vol) | vol.112 |
| Number (no) | no.298 |
| Page | pp.39-44 |
| #Pages | 6 |
| Date of Issue | 2012-11-09 (NC) |
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