Paper Abstract and Keywords |
Presentation |
2021-05-28 11:35
Software Framework Design for Machine Learning System Reliability Mitsunari Kobayashi, Daisuke Komaki (Hitachi) R2021-3 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Recently, enterprise software featuring Machine Learning (AI software) has widely adopted. Since behavior of AI software is determined recursively from the data used for learning, it has a different nature from non-AI software whose behavior is determined by static specification. To maintain the quality of AI software, there exists difficulty to design and develop software modules for managing the software quality according to changes in users’ requirements and incoming data through long-term operation. In the development of AI software, addition to a module to detect quality degradation by statistically monitoring the certainty of model inferences, it is necessary to individually design and develop the software modules, such as generation of training data set and the control of retraining process. In this study, we propose a software framework that facilitates the integration into AI software by the software modules as the standard ones for AI software. By using the proposed framework, software developers can easily develop a reliable AI software which is robust to changes in users’ requirements and incoming data. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Machine Learning / Artificial Intelligence / Application Framework / Reliability / CI/CD / Software Framerwork / / |
Reference Info. |
IEICE Tech. Rep., vol. 121, no. 47, R2021-3, pp. 13-18, May 2021. |
Paper # |
R2021-3 |
Date of Issue |
2021-05-21 (R) |
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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R2021-3 |
Conference Information |
Committee |
R |
Conference Date |
2021-05-28 - 2021-05-28 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Online |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Software Reliability, Reliability General |
Paper Information |
Registration To |
R |
Conference Code |
2021-05-R |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Software Framework Design for Machine Learning System Reliability |
Sub Title (in English) |
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Machine Learning |
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Artificial Intelligence |
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Application Framework |
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Reliability |
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CI/CD |
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Software Framerwork |
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1st Author's Name |
Mitsunari Kobayashi |
1st Author's Affiliation |
Hitachi, Ltd. (Hitachi) |
2nd Author's Name |
Daisuke Komaki |
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Hitachi, Ltd. (Hitachi) |
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Speaker |
Author-1 |
Date Time |
2021-05-28 11:35:00 |
Presentation Time |
25 minutes |
Registration for |
R |
Paper # |
R2021-3 |
Volume (vol) |
vol.121 |
Number (no) |
no.47 |
Page |
pp.13-18 |
#Pages |
6 |
Date of Issue |
2021-05-21 (R) |
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