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| Presentation | 2016-11-17 14:00 Empirical risk minimization for interval data and its applications to privacy preservations Hiroyuki Hanada, Toshiyuki Takada, Atsushi Shibagaki (NITech), Jun Sakuma (Univ. of Tsukuba), Ichiro Takeuchi (NITech)  IBISML2016-89 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In this research, for machine learning tasks, we consider that the values in the training data are given as intervals and that we compute the corresponding interval of the training result, aiming at applying it for privacy preservation tasks. An existing approach of solving machine learning problems for interval data is the interval analysis; however, the computation may be slow and the results may not converge for true results. In this research, for empirical risk minimization problems with the strong convexity, we propose a fast method computing the lower and the upper bounds of the interval of the training result, which we call the ``quick interval analysis''. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Privacy preserving machine learning / Quick interval analysis / Empirical risk minimization / Strongly convex functions / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 116, no. 300, IBISML2016-89, pp. 305-312, Nov. 2016. | |
| Paper # | IBISML2016-89 | |
| Date of Issue | 2016-11-09 (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 | IBISML2016-89 |
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| Conference Information | |
| Committee | IBISML |
| Conference Date | 2016-11-16 - 2016-11-18 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Kyoto Univ. |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Information-Based Induction Science Workshop (IBIS2016) |
| Paper Information | |
| Registration To | IBISML |
| Conference Code | 2016-11-IBISML |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Empirical risk minimization for interval data and its applications to privacy preservations |
| Sub Title (in English) | |
| Keyword(1) | Privacy preserving machine learning |
| Keyword(2) | Quick interval analysis |
| Keyword(3) | Empirical risk minimization |
| Keyword(4) | Strongly convex functions |
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| 1st Author's Name | Hiroyuki Hanada |
| 1st Author's Affiliation | Nagoya Institute of Technology (NITech) |
| 2nd Author's Name | Toshiyuki Takada |
| 2nd Author's Affiliation | Nagoya Institute of Technology (NITech) |
| 3rd Author's Name | Atsushi Shibagaki |
| 3rd Author's Affiliation | Nagoya Institute of Technology (NITech) |
| 4th Author's Name | Jun Sakuma |
| 4th Author's Affiliation | University of Tsukuba (Univ. of Tsukuba) |
| 5th Author's Name | Ichiro Takeuchi |
| 5th Author's Affiliation | Nagoya Institute of Technology (NITech) |
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| Speaker | Author-1 |
| Date Time | 2016-11-17 14:00:00 |
| Presentation Time | 180 minutes |
| Registration for | IBISML |
| Paper # | IBISML2016-89 |
| Volume (vol) | vol.116 |
| Number (no) | no.300 |
| Page | pp.305-312 |
| #Pages | 8 |
| Date of Issue | 2016-11-09 (IBISML) |
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