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| Presentation | 2016-03-18 11:05 Block-sparse Extensions of Recovery Conditions of Overcomplete Dictionaries Yasushi Terazono, Kenji Yamanishi (UTokyo)  IBISML2015-101 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In overcomplete dictionary learning problems, observed data are modeled as products of overcomplete dictionaries and sparse signal sources, and both dictionaries and sources are estimated from data. Recent researches have shown that given a set of sufficient conditions, it is possible to obtain approximations of dictionaries with a certain error bound with a certain probability. In this paper, we extend a part of reconstruction theorems shown by Agarwal et al. to the case of block-sparse modeling, as an initial step of constructing an exact recovery theory for block-sparse cases. Agarwal et al. used inner product of data samples to quantify the degree of similarity between samples; however, under block-sparse context, an inner product of a pair of data samples does not properly evaluate the degree of similarity in the case of block-sparse. We extended or modified the assumptions on dictionary, signal sources, similarity measure so that sample similarity and commonality of non-zero blocks are properly associated under block-sparse context. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | dictionary learning / overcomplete / block-sparse / / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 115, no. 511, IBISML2015-101, pp. 55-58, March 2016. | |
| Paper # | IBISML2015-101 | |
| Date of Issue | 2016-03-10 (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 | IBISML2015-101 |
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| Conference Information | |
| Committee | IBISML |
| Conference Date | 2016-03-17 - 2016-03-18 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Institute of Statistical Mathematics |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Statistical Mathematics, Machine Learning, Data Mining, etc. |
| Paper Information | |
| Registration To | IBISML |
| Conference Code | 2016-03-IBISML |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Block-sparse Extensions of Recovery Conditions of Overcomplete Dictionaries |
| Sub Title (in English) | |
| Keyword(1) | dictionary learning |
| Keyword(2) | overcomplete |
| Keyword(3) | block-sparse |
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| 1st Author's Name | Yasushi Terazono |
| 1st Author's Affiliation | The University of Tokyo (UTokyo) |
| 2nd Author's Name | Kenji Yamanishi |
| 2nd Author's Affiliation | The University of Tokyo (UTokyo) |
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| Speaker | Author-1 |
| Date Time | 2016-03-18 11:05:00 |
| Presentation Time | 25 minutes |
| Registration for | IBISML |
| Paper # | IBISML2015-101 |
| Volume (vol) | vol.115 |
| Number (no) | no.511 |
| Page | pp.55-58 |
| #Pages | 4 |
| Date of Issue | 2016-03-10 (IBISML) |
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