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Article

Transductive regression piloted by inter-manifold relations

Authors:

Jianzhuang Liu,

Xiaoou TangAuthors Info & Claims

ICML '07: Proceedings of the 24th international conference on Machine learning

Pages 967 - 974

https://doi.org/10.1145/1273496.1273618

Published: 20 June 2007 Publication History

Abstract

In this paper, we present a novel semisupervised regression algorithm working on multiclass data that may lie on multiple manifolds. Unlike conventional manifold regression algorithms that do not consider the class distinction of samples, our method introduces the class information to the regression process and tries to exploit the similar configurations shared by the label distribution of multi-class data. To utilize the correlations among data from different classes, we develop a cross-manifold label propagation process and employ labels from different classes to enhance the regression performance. The interclass relations are coded by a set of intermanifold graphs and a regularization item is introduced to impose inter-class smoothness on the possible solutions. In addition, the algorithm is further extended with the kernel trick for predicting labels of the out-of-sample data even without class information. Experiments on both synthesized data and real world problems validate the effectiveness of the proposed framework for semisupervised regression.

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Cited By

Xu RLiu XXie YYuan DYang YZhang HHuang LRichardson I(2014)A gaussian fields based mining method for semi-automating staff assignment in workflow applicationProceedings of the 2014 International Conference on Software and System Process10.1145/2600821.2600843(178-182)Online publication date: 26-May-2014
https://dl.acm.org/doi/10.1145/2600821.2600843
Saxena ADriemeyer JNg A(2009)Learning 3-D object orientation from imagesProceedings of the 2009 IEEE international conference on Robotics and Automation10.5555/1703775.1704134(4266-4272)Online publication date: 12-May-2009
https://dl.acm.org/doi/10.5555/1703775.1704134
Saxena ADriemeyer JNg A(2009)Learning 3-D object orientation from images2009 IEEE International Conference on Robotics and Automation10.1109/ROBOT.2009.5152855(794-800)Online publication date: May-2009
https://doi.org/10.1109/ROBOT.2009.5152855

Transductive regression piloted by inter-manifold relations
1. Computing methodologies

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Published In

cover image ACM Other conferences

ICML '07: Proceedings of the 24th international conference on Machine learning

June 2007

1233 pages

ISBN:9781595937933

DOI:10.1145/1273496

Editor:
Zoubin Ghahramani
University of Cambridge, United Kingdom

Copyright © 2007 ACM.

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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Machine Learning Journal

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Association for Computing Machinery

New York, NY, United States

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Published: 20 June 2007

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ICML '07 & ILP '07

Sponsor:

ICML '07 & ILP '07: The 24th Annual International Conference on Machine Learning held in conjunction with the 2007 International Conference on Inductive Logic Programming

June 20 - 24, 2007

Oregon, Corvalis, USA

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Cited By

Xu RLiu XXie YYuan DYang YZhang HHuang LRichardson I(2014)A gaussian fields based mining method for semi-automating staff assignment in workflow applicationProceedings of the 2014 International Conference on Software and System Process10.1145/2600821.2600843(178-182)Online publication date: 26-May-2014
https://dl.acm.org/doi/10.1145/2600821.2600843
Saxena ADriemeyer JNg A(2009)Learning 3-D object orientation from imagesProceedings of the 2009 IEEE international conference on Robotics and Automation10.5555/1703775.1704134(4266-4272)Online publication date: 12-May-2009
https://dl.acm.org/doi/10.5555/1703775.1704134
Saxena ADriemeyer JNg A(2009)Learning 3-D object orientation from images2009 IEEE International Conference on Robotics and Automation10.1109/ROBOT.2009.5152855(794-800)Online publication date: May-2009
https://doi.org/10.1109/ROBOT.2009.5152855

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