Paper Abstract and Keywords |
Presentation |
2023-02-22 09:45
Probabilistic Approach towards Theoretical Understanding for Adversarial Training Soichiro Kumano (UTokyo), Hiroshi Kera (Chiba Univ.), Toshihiko Yamasaki (UTokyo) ITS2022-59 IE2022-76 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In this paper, we provide the first theoretical analysis of the training dynamics of adversarial training of deep neural networks in a mean field view. To this end, we propose a new mean field theory, which allows us to study adversarial training from various aspects. Particularly, we derive tight upper bounds for adversarial loss with various norms, prove that networks are not adversarially trainable without shortcuts except for restrictive cases, show that adversarial training degrades the expressibility of a network, and the network width is an important factor to alleviate this. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Adversarial Training / Adversarial Examples / Mean Field Theory / Probabilistic Theory / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 122, no. 385, IE2022-76, pp. 95-100, Feb. 2023. |
Paper # |
IE2022-76 |
Date of Issue |
2023-02-14 (ITS, IE) |
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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ITS2022-59 IE2022-76 |
Conference Information |
Committee |
IE ITS ITE-MMS ITE-ME ITE-AIT |
Conference Date |
2023-02-21 - 2023-02-22 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Hokkaido Univ. |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Image Processing, etc. |
Paper Information |
Registration To |
IE |
Conference Code |
2023-02-IE-ITS-MMS-ME-AIT |
Language |
English (Japanese title is available) |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Probabilistic Approach towards Theoretical Understanding for Adversarial Training |
Sub Title (in English) |
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Keyword(1) |
Adversarial Training |
Keyword(2) |
Adversarial Examples |
Keyword(3) |
Mean Field Theory |
Keyword(4) |
Probabilistic Theory |
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1st Author's Name |
Soichiro Kumano |
1st Author's Affiliation |
The University of Tokyo (UTokyo) |
2nd Author's Name |
Hiroshi Kera |
2nd Author's Affiliation |
Chiba University (Chiba Univ.) |
3rd Author's Name |
Toshihiko Yamasaki |
3rd Author's Affiliation |
The University of Tokyo (UTokyo) |
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Speaker |
Author-1 |
Date Time |
2023-02-22 09:45:00 |
Presentation Time |
15 minutes |
Registration for |
IE |
Paper # |
ITS2022-59, IE2022-76 |
Volume (vol) |
vol.122 |
Number (no) |
no.384(ITS), no.385(IE) |
Page |
pp.95-100 |
#Pages |
6 |
Date of Issue |
2023-02-14 (ITS, IE) |
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