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Semi-supervised metric learning by maximizing constraint margin

Authors:

Fei Wang,

Shouchun Chen,

Changshui Zhang,

Tao LiAuthors Info & Claims

CIKM '08: Proceedings of the 17th ACM conference on Information and knowledge management

Pages 1457 - 1458

https://doi.org/10.1145/1458082.1458331

Published: 26 October 2008 Publication History

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Abstract

Distance metric learning is an old problem that has been researched in the supervised learning field for a very long time. In this paper, we consider the problem of learning a proper distance metric under the guidance of some weak supervisory information. Specifically, those information are in the form of pairwise constraints which specify whether a pair of data points are in the same class (must link constraints) or in the different classes (cannot link constraints). Given those constraints, our algorithm aims to learn a distance metric under which the points with must link constraints are pushed as close as possible, while simultaneously the points with cannot link constraints are pulled away as far as possible. Finally the experimental results are presented to show the effectiveness of our method.

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Chang CHuang H(2019)Automatic Tuning of the RBF Kernel Parameter for Batch-Mode Active Learning Algorithms: A Scalable FrameworkIEEE Transactions on Cybernetics10.1109/TCYB.2018.286986149:12(4460-4472)Online publication date: Dec-2019
https://doi.org/10.1109/TCYB.2018.2869861
Khan MDeb KChowdhury LChakroborty P(2015)LiCo: A supervised method for measurement of DNA heterogeneity2015 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE)10.1109/WIECON-ECE.2015.7443930(329-332)Online publication date: Dec-2015
https://doi.org/10.1109/WIECON-ECE.2015.7443930
Fei Wang Jimeng Sun (2015)PSF: A Unified Patient Similarity Evaluation Framework Through Metric Learning With Weak SupervisionIEEE Journal of Biomedical and Health Informatics10.1109/JBHI.2015.242536519:3(1053-1060)Online publication date: May-2015
https://doi.org/10.1109/JBHI.2015.2425365
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Index Terms

Semi-supervised metric learning by maximizing constraint margin
1. Computing methodologies
  1. Machine learning
    1. Learning settings
2. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Clustering and classification
  2. Information systems applications
    1. Data mining
      1. Clustering

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Information & Contributors

Information

Published In

CIKM '08: Proceedings of the 17th ACM conference on Information and knowledge management

October 2008

1562 pages

ISBN:9781595939913

DOI:10.1145/1458082

General Chair:
James G. Shanahan
Church and Duncan Group Inc, USA
,
Program Chairs:
Sihem Amer-Yahia
Yahoo! Research, USA
,
Ioana Manolescu
INRIA, France
,
Yi Zhang
University of California, Santa Cruz, USA
,
David A. Evans
JustSystems Evans Research, USA
,
Alek Kolcz
Microsoft Live Labs, USA
,
Key-Sun Choi
KAIST, Korea
,
Abdur Chowdury
Twitter, USA

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 October 2008

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CIKM08: Conference on Information and Knowledge Management

October 26 - 30, 2008

California, Napa Valley, USA

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Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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Cited By

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Chang CHuang H(2019)Automatic Tuning of the RBF Kernel Parameter for Batch-Mode Active Learning Algorithms: A Scalable FrameworkIEEE Transactions on Cybernetics10.1109/TCYB.2018.286986149:12(4460-4472)Online publication date: Dec-2019
https://doi.org/10.1109/TCYB.2018.2869861
Khan MDeb KChowdhury LChakroborty P(2015)LiCo: A supervised method for measurement of DNA heterogeneity2015 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE)10.1109/WIECON-ECE.2015.7443930(329-332)Online publication date: Dec-2015
https://doi.org/10.1109/WIECON-ECE.2015.7443930
Fei Wang Jimeng Sun (2015)PSF: A Unified Patient Similarity Evaluation Framework Through Metric Learning With Weak SupervisionIEEE Journal of Biomedical and Health Informatics10.1109/JBHI.2015.242536519:3(1053-1060)Online publication date: May-2015
https://doi.org/10.1109/JBHI.2015.2425365
Wang FSun J(2015)Survey on distance metric learning and dimensionality reduction in data miningData Mining and Knowledge Discovery10.1007/s10618-014-0356-z29:2(534-564)Online publication date: 1-Mar-2015
https://dl.acm.org/doi/10.1007/s10618-014-0356-z
Zhao Zhang Chow TMingbo Zhao (2013)M-Isomap: Orthogonal Constrained Marginal Isomap for Nonlinear Dimensionality ReductionIEEE Transactions on Cybernetics10.1109/TSMCB.2012.220290143:1(180-191)Online publication date: Feb-2013
https://doi.org/10.1109/TSMCB.2012.2202901
Liu CHsaio WLee CChen C(2013)Clustering tagged documents with labeled and unlabeled documentsInformation Processing and Management: an International Journal10.1016/j.ipm.2012.12.00449:3(596-606)Online publication date: 1-May-2013
https://dl.acm.org/doi/10.1016/j.ipm.2012.12.004
Lu YZhao WYan HLi X(2013)A metric learning based approach to evaluate task-specific time series similarityProceedings of the 14th international conference on Web-Age Information Management10.1007/978-3-642-38562-9_32(314-325)Online publication date: 14-Jun-2013
https://dl.acm.org/doi/10.1007/978-3-642-38562-9_32
Wang FSun JEbadollahi S(2012)Composite distance metric integration by leveraging multiple experts' inputs and its application in patient similarity assessmentStatistical Analysis and Data Mining10.5555/3160825.31608305:1(54-69)Online publication date: 1-Feb-2012
https://dl.acm.org/doi/10.5555/3160825.3160830
Sun JWang FHu JEdabollahi S(2012)Supervised patient similarity measure of heterogeneous patient recordsACM SIGKDD Explorations Newsletter10.1145/2408736.240874014:1(16-24)Online publication date: 10-Dec-2012
https://dl.acm.org/doi/10.1145/2408736.2408740
Shang FJiao LLiu Y(2012)Integrating Spectral Kernel Learning and Constraints in Semi-Supervised ClassificationNeural Processing Letters10.1007/s11063-012-9224-236:2(101-115)Online publication date: 1-Oct-2012
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