Paper Abstract and Keywords |
Presentation |
2021-12-17 14:45
Data Selection for Efficient Deep Learning Ryota Higashi, Toshikazu Wada (Wakayama Univ.) PRMU2021-51 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
We are investigating the method to sample the important data from the whole dataset for efficient training of Deep Neural Networks. In this report, we compare the accuracy of image classifiers trained from reduced datasets: sampled near the decision boundaries, sampled uniformly over the latent space, and sampled randomly. Experimental results imply that the optimal sampling varies depending on the number of samples, and the data selection criteria should be changed accordingly. Also, we introduce distillation to recover the accuracy degradation by the data reduction and evaluate its effect. Data selection can be applied to many problems: prototyping, active learning, and weighted learning. Findings in this report can be utilized to produce better solution of them. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Deep Learning / Data Selection / Image Classification / Distillation / Active Learning / / / |
Reference Info. |
IEICE Tech. Rep., vol. 121, no. 304, PRMU2021-51, pp. 148-153, Dec. 2021. |
Paper # |
PRMU2021-51 |
Date of Issue |
2021-12-09 (PRMU) |
ISSN |
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) |
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PRMU2021-51 |
Conference Information |
Committee |
PRMU |
Conference Date |
2021-12-16 - 2021-12-17 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Online |
Topics (in Japanese) |
(See Japanese page) |
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Paper Information |
Registration To |
PRMU |
Conference Code |
2021-12-PRMU |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Data Selection for Efficient Deep Learning |
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Deep Learning |
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Data Selection |
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Image Classification |
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Distillation |
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Active Learning |
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1st Author's Name |
Ryota Higashi |
1st Author's Affiliation |
Wakayama University (Wakayama Univ.) |
2nd Author's Name |
Toshikazu Wada |
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Wakayama University (Wakayama Univ.) |
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Speaker |
Author-1 |
Date Time |
2021-12-17 14:45:00 |
Presentation Time |
15 minutes |
Registration for |
PRMU |
Paper # |
PRMU2021-51 |
Volume (vol) |
vol.121 |
Number (no) |
no.304 |
Page |
pp.148-153 |
#Pages |
6 |
Date of Issue |
2021-12-09 (PRMU) |
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