NDLI: Twin Gaussian Processes for Binary Classification

Content Provider	IEEE Xplore Digital Library
Author	Jianjun He Hong Gu Shaorui Jiang
Copyright Year	2011
Abstract	Gaussian process classifiers (GPCs) have recently attracted more and more attention from the machine learning community. However, because the posterior needs to be approximated by using a tractable Gaussian distribution, they usually suffer from high computational cost which is prohibitive for practical applications. In this paper, we present a new Gaussian process model termed as twin Gaussian processes for binary classification. The basic idea is to make predictions based on two latent functions with Gaussian process prior, each of which is close to one of the two classes and is as far as possible from the other. Being compared with the published GPCs, the proposed algorithm allows for an explicit inference based on analytical methods, thereby avoiding the high computational cost caused by approximating the posterior with Gaussian distribution. Experimental results on several benchmark data sets show that the proposed algorithm is valid and can achieve superior performance to the published algorithms.
Starting Page	1074
Ending Page	1079
File Size	223754
Page Count	6
File Format	PDF
ISBN	9781457720758
ISSN	15504786
DOI	10.1109/ICDM.2011.149
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-12-11
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Gaussian processes Computational modeling Covariance matrix Approximation methods Computational efficiency Approximation algorithms Training Kernel machine Twin Gaussian processes Binary classification Bayesian methods
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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