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| Presentation | 2017-11-09 13:00 [Poster Presentation] Real Log Canonical Threshold of Stochastic Matrix Factorization and its Application to Bayesian Learning Naoki Hayashi, Sumio Watanabe (TokyoTech)  IBISML2017-38 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In stochastic matrix factorization (SMF), we deal with problems that we predict an observed stochastic matrix as a product of two stochastic matrices. This problem is equivalent to statistically estimating the rank when a transition matrix in such a Markov chain is predicted as a lower rank stochastic matrix. From statistical point of view, since a map from parameter set to a probability distribution set is not one-to-one, it is a non-regular statistical model and theoretical prediction accuracy has not been clarified. In this paper, we mathematically evaluate the real log canonical threshold of SMF and give an upper bound of the generalization error at Bayesian learning. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Stochastic matrix factorization (SMF) / Singular model / Real log canonical threshold / Markov chain / Bayesian learning / Bayesian inference / / | |
| Reference Info. | IEICE Tech. Rep., vol. 117, no. 293, IBISML2017-38, pp. 23-30, Nov. 2017. | |
| Paper # | IBISML2017-38 | |
| 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) | |
| Download PDF | IBISML2017-38 |
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| 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) | Real Log Canonical Threshold of Stochastic Matrix Factorization and its Application to Bayesian Learning |
| Sub Title (in English) | |
| Keyword(1) | Stochastic matrix factorization (SMF) |
| Keyword(2) | Singular model |
| Keyword(3) | Real log canonical threshold |
| Keyword(4) | Markov chain |
| Keyword(5) | Bayesian learning |
| Keyword(6) | Bayesian inference |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Naoki Hayashi |
| 1st Author's Affiliation | Tokyo Institute of Technology (TokyoTech) |
| 2nd Author's Name | Sumio Watanabe |
| 2nd Author's Affiliation | Tokyo Institute of Technology (TokyoTech) |
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| Speaker | Author-1 |
| Date Time | 2017-11-09 13:00:00 |
| Presentation Time | 150 minutes |
| Registration for | IBISML |
| Paper # | IBISML2017-38 |
| Volume (vol) | vol.117 |
| Number (no) | no.293 |
| Page | pp.23-30 |
| #Pages | 8 |
| Date of Issue | 2017-11-02 (IBISML) |
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