Paper Abstract and Keywords |
Presentation |
2021-06-28 16:10
More Powerful and General Selective Inference for Stepwise Feature Selection using Homotopy Method Kazuya Sugiyama (Nitech), Vo Nguyen Le Duy, Ichiro Takeuchi (Nitech/RIKEN) NC2021-8 IBISML2021-8 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Conditional selective inference (SI) has been actively studied as a new statistical inference framework for data-driven hypotheses.
The basic idea of conditional SI is to make inferences conditional on the selection event characterized by a set of linear and/or quadratic inequalities.
Conditional SI has been mainly studied in the context of feature selection such as stepwise feature selection (SFS).
The main limitation of the existing conditional SI methods is the loss of power due to over-conditioning, which is required for computational tractability.
In this study, we develop a more powerful and general conditional SI method for SFS using the homotopy method which enables us to overcome this limitation.
We conduct several experiments to demonstrate the effectiveness and efficiency of the proposed method. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
conditional SI / data-driven hypothesis / stepwise feature selection / homotopy continuation / statistical power / / / |
Reference Info. |
IEICE Tech. Rep., vol. 121, no. 80, IBISML2021-8, pp. 55-61, June 2021. |
Paper # |
IBISML2021-8 |
Date of Issue |
2021-06-21 (NC, IBISML) |
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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NC2021-8 IBISML2021-8 |
Conference Information |
Committee |
NC IBISML IPSJ-BIO IPSJ-MPS |
Conference Date |
2021-06-28 - 2021-06-30 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Online |
Topics (in Japanese) |
(See Japanese page) |
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Paper Information |
Registration To |
IBISML |
Conference Code |
2021-06-NC-IBISML-BIO-MPS |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
More Powerful and General Selective Inference for Stepwise Feature Selection using Homotopy Method |
Sub Title (in English) |
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Keyword(1) |
conditional SI |
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data-driven hypothesis |
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stepwise feature selection |
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homotopy continuation |
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statistical power |
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1st Author's Name |
Kazuya Sugiyama |
1st Author's Affiliation |
Nagoya Institute of Technology (Nitech) |
2nd Author's Name |
Vo Nguyen Le Duy |
2nd Author's Affiliation |
Nagoya Institute of Technology/RIKEN (Nitech/RIKEN) |
3rd Author's Name |
Ichiro Takeuchi |
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Nagoya Institute of Technology/RIKEN (Nitech/RIKEN) |
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Speaker |
Author-1 |
Date Time |
2021-06-28 16:10:00 |
Presentation Time |
25 minutes |
Registration for |
IBISML |
Paper # |
NC2021-8, IBISML2021-8 |
Volume (vol) |
vol.121 |
Number (no) |
no.79(NC), no.80(IBISML) |
Page |
pp.55-61 |
#Pages |
7 |
Date of Issue |
2021-06-21 (NC, IBISML) |
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