Paper Abstract and Keywords |
Presentation |
2018-11-05 15:10
[Poster Presentation]
Active Learning in Sparse Linear Regression Models via Selective Inference Yuta Umezu (NIT), Ichiro Takeuchi (NIT/NIMS/RIKEN) IBISML2018-95 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In order to efficiently estimate interested parameter, one can design sampling strategy by defining some criterion on the optimality. This is a problem of so-called active learning or optimal design of experiment.
On the other hand, we expect that we can estimate it more efficiently by conducting model selection method when the number of feature is large. However, since the estimator depends on the result of model selection, the problem of selection bias would be occur when we consider the model selection and active learning simultaneously. In this paper, we propose novel active learning method after model selection by exploiting the idea of selective inference. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Active Learning / Lasso / Model Selection / Selective $A$-optimality / Selective Inference / / / |
Reference Info. |
IEICE Tech. Rep., vol. 118, no. 284, IBISML2018-95, pp. 381-388, Nov. 2018. |
Paper # |
IBISML2018-95 |
Date of Issue |
2018-10-29 (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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IBISML2018-95 |
Conference Information |
Committee |
IBISML |
Conference Date |
2018-11-05 - 2018-11-07 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Hokkaido Citizens Activites Center (Kaderu 2.7) |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Information-Based Induction Science Workshop (IBIS2018) |
Paper Information |
Registration To |
IBISML |
Conference Code |
2018-11-IBISML |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Active Learning in Sparse Linear Regression Models via Selective Inference |
Sub Title (in English) |
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Keyword(1) |
Active Learning |
Keyword(2) |
Lasso |
Keyword(3) |
Model Selection |
Keyword(4) |
Selective $A$-optimality |
Keyword(5) |
Selective Inference |
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1st Author's Name |
Yuta Umezu |
1st Author's Affiliation |
Nagoya Institute of Technology (NIT) |
2nd Author's Name |
Ichiro Takeuchi |
2nd Author's Affiliation |
Nagoya Institute of Technology/National Institute for Materials Science/RIKEN (NIT/NIMS/RIKEN) |
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Speaker |
Author-1 |
Date Time |
2018-11-05 15:10:00 |
Presentation Time |
180 minutes |
Registration for |
IBISML |
Paper # |
IBISML2018-95 |
Volume (vol) |
vol.118 |
Number (no) |
no.284 |
Page |
pp.381-388 |
#Pages |
8 |
Date of Issue |
2018-10-29 (IBISML) |
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