Paper Abstract and Keywords |
Presentation |
2011-11-10 15:45
A convex formulations of learning from crowds Hiroshi Kajino, Hisashi Kashima (UT) IBISML2011-76 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
It has attracted considerable attention to use crowdsourcing services
to collect a large amount of labeled data for machine learning,
since crowdsourcing services allow one to ask the general public to
label data at very low cost through the Internet.
The use of crowdsourcing has introduced a new challenge in machine
learning, that is, coping with low quality of crowd-generated data.
There have been many recent attempts to address the quality problem of
multiple labelers, however, there is a serious drawback in the existing approaches, that is non-convexity of the objective function.
Most of the existing methods consider true labels as latent variables,
which results in non-convex optimization problems.
In this paper, we propose a convex optimization formulation of learning
from crowds by introducing personal models of individual crowds without
estimating true labels.
We also devise an efficient iterative method for solving the convex
optimization problem by exploiting conditional independence structures
in multiple classifiers. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
crowdsourcing / convex optimization / / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 111, no. 275, IBISML2011-76, pp. 231-236, Nov. 2011. |
Paper # |
IBISML2011-76 |
Date of Issue |
2011-11-02 (IBISML) |
ISSN |
Print edition: ISSN 0913-5685 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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IBISML2011-76 |
Conference Information |
Committee |
IBISML |
Conference Date |
2011-11-09 - 2011-11-11 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Nara Womens Univ. |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
The 14th IBIS workshop |
Paper Information |
Registration To |
IBISML |
Conference Code |
2011-11-IBISML |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
A convex formulations of learning from crowds |
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crowdsourcing |
Keyword(2) |
convex optimization |
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1st Author's Name |
Hiroshi Kajino |
1st Author's Affiliation |
University of Tokyo (UT) |
2nd Author's Name |
Hisashi Kashima |
2nd Author's Affiliation |
University of Tokyo (UT) |
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Speaker |
1 |
Date Time |
2011-11-10 15:45:00 |
Presentation Time |
180 |
Registration for |
IBISML |
Paper # |
IEICE-IBISML2011-76 |
Volume (vol) |
IEICE-111 |
Number (no) |
no.275 |
Page |
pp.231-236 |
#Pages |
IEICE-6 |
Date of Issue |
IEICE-IBISML-2011-11-02 |
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