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| Presentation | 2014-11-17 17:00 [Poster Presentation] Direct Density-Derivative Estimation and Its Application in KL-Divergence Approximation Hiroaki Sasaki (Univ. of Tokyo), Yung-Kyun Noh (KAIST), Masashi Sugiyama (Univ. of Tokyo)  IBISML2014-52 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Estimation of density derivatives is a versatile tool in statistical data analysis. A naive approach is to first estimate the density and then compute its derivative. However, such a two-step approach does not work well because a good density estimator does not necessarily mean a good density-derivative estimator. In this paper, we give a direct method to approximate the density derivative without estimating the density itself. Our proposed estimator allows analytic and computationally efficient approximation of multi-dimensional high-order density derivatives, with the ability that all hyper-parameters can be chosen objectively by cross-validation. We further show that the proposed density-derivative estimator is useful in improving the accuracy of non-parametric KL-divergence estimation via metric learning. The practical superiority of the proposed method is experimentally demonstrated in change detection and feature selection. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | density-derivative estimation / higher-order density-derivative / non-parametric estimation / Kullback- -Leibler divergence / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 114, no. 306, IBISML2014-52, pp. 133-140, Nov. 2014. | |
| Paper # | IBISML2014-52 | |
| Date of Issue | 2014-11-10 (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 | IBISML2014-52 |
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| Conference Information | |
| Committee | IBISML |
| Conference Date | 2014-11-17 - 2014-11-19 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Nagoya Univ. |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | IBISML |
| Conference Code | 2014-11-IBISML |
| Language | English (Japanese title is available) |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Direct Density-Derivative Estimation and Its Application in KL-Divergence Approximation |
| Sub Title (in English) | |
| Keyword(1) | density-derivative estimation |
| Keyword(2) | higher-order density-derivative |
| Keyword(3) | non-parametric estimation |
| Keyword(4) | Kullback- -Leibler divergence |
| Keyword(5) | |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Hiroaki Sasaki |
| 1st Author's Affiliation | The University of Tokyo (Univ. of Tokyo) |
| 2nd Author's Name | Yung-Kyun Noh |
| 2nd Author's Affiliation | Korea Advanced Institute of Science and Technology (KAIST) |
| 3rd Author's Name | Masashi Sugiyama |
| 3rd Author's Affiliation | The University of Tokyo (Univ. of Tokyo) |
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| Speaker | Author-1 |
| Date Time | 2014-11-17 17:00:00 |
| Presentation Time | 180 minutes |
| Registration for | IBISML |
| Paper # | IBISML2014-52 |
| Volume (vol) | vol.114 |
| Number (no) | no.306 |
| Page | pp.133-140 |
| #Pages | 8 |
| Date of Issue | 2014-11-10 (IBISML) |
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