Paper Abstract and Keywords |
Presentation |
2019-06-17 15:25
Optimal Estimating the Number of Change Points for Sources with Piecewise Constant parameters under Bayesian Criterion Kairi Suzuki, Akira Kamatsuka, Toshiyasu Matsushima (Waseda Univ.) IBISML2019-6 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
The problem of estimating the number of the change points is an important problem in various real problems.There have been studies on this problem, in which the number of change points is estimated by maximizing the likelihood[4] and in which the prior distribution is assumed, using MAP estimation[6]. In [4], the estimated number of change points is not theoretically guaranteed.In [6], it takes the computational complexity in the order of $O¥left(2^{n-1}¥right)$ to estimate.In this study, we formulate an estimation problem of the number of change points in the statistical decision theory. Then we propose an optimal and efficient estimating algorithm of the number of change points under bayesian criterion.
The algorithm take the computational complexity in the order of $O¥left(n^{3}¥right)$ under some assumptions. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Change points detection / Estimating the number of change points / Sources with piecewise constant parameters / Statistical Decision Theory / Bayes risk / Bayes rule / / |
Reference Info. |
IEICE Tech. Rep., vol. 119, no. 89, IBISML2019-6, pp. 35-41, June 2019. |
Paper # |
IBISML2019-6 |
Date of Issue |
2019-06-10 (IBISML) |
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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IBISML2019-6 |
Conference Information |
Committee |
NC IBISML IPSJ-MPS IPSJ-BIO |
Conference Date |
2019-06-17 - 2019-06-19 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Okinawa Institute of Science and Technology |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Neurocomputing, Machine Learning Approach to Biodata Mining, and General |
Paper Information |
Registration To |
IBISML |
Conference Code |
2019-06-NC-IBISML-MPS-BIO |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Optimal Estimating the Number of Change Points for Sources with Piecewise Constant parameters under Bayesian Criterion |
Sub Title (in English) |
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Keyword(1) |
Change points detection |
Keyword(2) |
Estimating the number of change points |
Keyword(3) |
Sources with piecewise constant parameters |
Keyword(4) |
Statistical Decision Theory |
Keyword(5) |
Bayes risk |
Keyword(6) |
Bayes rule |
Keyword(7) |
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Keyword(8) |
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1st Author's Name |
Kairi Suzuki |
1st Author's Affiliation |
Waseda University (Waseda Univ.) |
2nd Author's Name |
Akira Kamatsuka |
2nd Author's Affiliation |
Waseda University (Waseda Univ.) |
3rd Author's Name |
Toshiyasu Matsushima |
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Waseda University (Waseda Univ.) |
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Speaker |
Author-1 |
Date Time |
2019-06-17 15:25:00 |
Presentation Time |
25 minutes |
Registration for |
IBISML |
Paper # |
IBISML2019-6 |
Volume (vol) |
vol.119 |
Number (no) |
no.89 |
Page |
pp.35-41 |
#Pages |
7 |
Date of Issue |
2019-06-10 (IBISML) |