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PR
2008
151views more  PR 2008»
8 years 9 months ago
Constraint Score: A new filter method for feature selection with pairwise constraints
Feature selection is an important preprocessing step in mining high-dimensional data. Generally, supervised feature selection methods with supervision information are superior to ...
Daoqiang Zhang, Songcan Chen, Zhi-Hua Zhou
SDM
2004
SIAM
225views Data Mining» more  SDM 2004»
8 years 10 months ago
Active Semi-Supervision for Pairwise Constrained Clustering
Semi-supervised clustering uses a small amount of supervised data to aid unsupervised learning. One typical approach specifies a limited number of must-link and cannotlink constra...
Sugato Basu, Arindam Banerjee, Raymond J. Mooney
AAAI
2008
8 years 11 months ago
Constraint Projections for Ensemble Learning
It is well-known that diversity among base classifiers is crucial for constructing a strong ensemble. Most existing ensemble methods obtain diverse individual learners through res...
Daoqiang Zhang, Songcan Chen, Zhi-Hua Zhou, Qiang ...
ICMCS
2006
IEEE
115views Multimedia» more  ICMCS 2006»
9 years 3 months ago
People Identification with Limited Labels in Privacy-Protected Video
People identification is an essential task for video content analysis in a surveillance system. A good classifier, however, requires a large amount of training data, which may not...
Yi Chang, Rong Yan, Datong Chen, Jie Yang
ICDM
2007
IEEE
129views Data Mining» more  ICDM 2007»
9 years 3 months ago
Semi-supervised Clustering Using Bayesian Regularization
Text clustering is most commonly treated as a fully automated task without user supervision. However, we can improve clustering performance using supervision in the form of pairwi...
Zuobing Xu, Ram Akella, Mike Ching, Renjie Tang
IAT
2009
IEEE
9 years 3 months ago
Clustering with Constrained Similarity Learning
—This paper proposes a method of learning a similarity matrix from pairwise constraints for interactive clustering. The similarity matrix can be learned by solving an optimizatio...
Masayuki Okabe, Seiji Yamada
ICML
2007
IEEE
9 years 10 months ago
On the value of pairwise constraints in classification and consistency
In this paper we consider the problem of classification in the presence of pairwise constraints, which consist of pairs of examples as well as a binary variable indicating whether...
Jian Zhang, Rong Yan
CVPR
2008
IEEE
9 years 11 months ago
Constrained spectral clustering through affinity propagation
Pairwise constraints specify whether or not two samples should be in one cluster. Although it has been successful to incorporate them into traditional clustering methods, such as ...
Miguel Á. Carreira-Perpiñán, ...
CVPR
2004
IEEE
9 years 11 months ago
A Discriminative Learning Framework with Pairwise Constraints for Video Object Classification
In video object classification, insufficient labeled data may at times be easily augmented with pairwise constraints on sample points, i.e, whether they are in the same class or n...
Rong Yan, Jian Zhang, Jie Yang, Alexander G. Haupt...
ICCV
2009
IEEE
10 years 2 months ago
Optimal Correspondences from Pairwise Constraints
Correspondence problems are of great importance in computer vision. They appear as subtasks in many applications such as object recognition, merging partial 3D reconstructions a...
Olof Enqvist, Klas Josephson, Fredrik Kahl
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