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| Presentation | 2012-11-07 15:30 Propagating Labels via Sparse Combination of Multiple Graphs Masayuki Karasuyama, Hiroshi Mamitsuka (Kyoto Univ.)  IBISML2012-58 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Label propagation is a widely accepted approach in graph-based semi-supervised learning that predicts labels of nodes so that they are smooth over the input graph. We address the issue of combining multiple graphs under the framework of label propagation. The most unique feature of our approach is the sparsity of graph weights which allows to eliminate graphs irrelevant to classification automatically if they are inputted, and further to improve the predictive performance and provide the interpretability of the resultant integrated graphs. We provide an optimization problem formulation, giving weights over input graphs, and an efficient algorithm for solving the problem. We demonstrate the performance advantage and the clear interpretability of our approach through various synthetic and two real-world datasets. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Semi-supervised learning / label propagation / graph / sparsity / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 112, no. 279, IBISML2012-58, pp. 171-178, Nov. 2012. | |
| Paper # | IBISML2012-58 | |
| Date of Issue | 2012-10-31 (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 | IBISML2012-58 |
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| Conference Information | |
| Committee | IBISML |
| Conference Date | 2012-11-07 - 2012-11-09 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Bunkyo School Building, Tokyo Campus, Tsukuba Univ. |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | the 15th Information-Based Induction Sciences Workshop |
| Paper Information | |
| Registration To | IBISML |
| Conference Code | 2012-11-IBISML |
| Language | English (Japanese title is available) |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Propagating Labels via Sparse Combination of Multiple Graphs |
| Sub Title (in English) | |
| Keyword(1) | Semi-supervised learning |
| Keyword(2) | label propagation |
| Keyword(3) | graph |
| Keyword(4) | sparsity |
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| 1st Author's Name | Masayuki Karasuyama |
| 1st Author's Affiliation | Kyoto University (Kyoto Univ.) |
| 2nd Author's Name | Hiroshi Mamitsuka |
| 2nd Author's Affiliation | Kyoto University (Kyoto Univ.) |
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| Speaker | Author-1 |
| Date Time | 2012-11-07 15:30:00 |
| Presentation Time | 150 minutes |
| Registration for | IBISML |
| Paper # | IBISML2012-58 |
| Volume (vol) | vol.112 |
| Number (no) | no.279 |
| Page | pp.171-178 |
| #Pages | 8 |
| Date of Issue | 2012-10-31 (IBISML) |
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