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| Presentation | 2017-11-10 13:00 Safe Screening for Large Margin Metric Learning Tomoki Yoshida (NITech), Ichiro Takeuchi (NITech/NIMS/RIKEN), Masayuki Karasuyama (NITech/NIMS/JST)  IBISML2017-64 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Large margin metric learning learns the optimal Mahalanobis distance for classification problem based on the margin maximization principle. The loss function in this method is defined for triples of instances, called triplet. However, the number of triplets can be huge even for small datasets and it causes large computational cost for the optimization. In this paper, we propose safe triplet screening by which unnecessary triplets can be safely eliminated before or during learning without loosing the optimality. We analyze several types of screening rules derived by considering a region (bound) containing the optimal solution, and evaluate effectiveness of the proposed method by experiments on several benchmark datasets. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Mahalanobis distance / Safe Screening / Metric Learning / / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 117, no. 293, IBISML2017-64, pp. 219-226, Nov. 2017. | |
| Paper # | IBISML2017-64 | |
| 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 | IBISML2017-64 |
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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) | Safe Screening for Large Margin Metric Learning |
| Sub Title (in English) | |
| Keyword(1) | Mahalanobis distance |
| Keyword(2) | Safe Screening |
| Keyword(3) | Metric Learning |
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| 1st Author's Name | Tomoki Yoshida |
| 1st Author's Affiliation | Nagoya Institute of Technology (NITech) |
| 2nd Author's Name | Ichiro Takeuchi |
| 2nd Author's Affiliation | Nagoya Institute of Technology/National Institute for Material Science/Institute of Physical and Chemical Research (NITech/NIMS/RIKEN) |
| 3rd Author's Name | Masayuki Karasuyama |
| 3rd Author's Affiliation | Nagoya Institute of Technology/National Institute for Material Science/Japan Science and Technology Agency (NITech/NIMS/JST) |
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| Speaker | Author-1 |
| Date Time | 2017-11-10 13:00:00 |
| Presentation Time | 150 minutes |
| Registration for | IBISML |
| Paper # | IBISML2017-64 |
| Volume (vol) | vol.117 |
| Number (no) | no.293 |
| Page | pp.219-226 |
| #Pages | 8 |
| Date of Issue | 2017-11-02 (IBISML) |
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