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JMLR
2010
172views more  JMLR 2010»
13 years 4 months ago
Modeling annotator expertise: Learning when everybody knows a bit of something
Supervised learning from multiple labeling sources is an increasingly important problem in machine learning and data mining. This paper develops a probabilistic approach to this p...
Yan Yan, Rómer Rosales, Glenn Fung, Mark W....
TNN
2010
154views Management» more  TNN 2010»
13 years 4 months ago
Discriminative semi-supervised feature selection via manifold regularization
We consider the problem of semi-supervised feature selection, where we are given a small amount of labeled examples and a large amount of unlabeled examples. Since a small number ...
Zenglin Xu, Irwin King, Michael R. Lyu, Rong Jin
ICML
2005
IEEE
14 years 10 months ago
Supervised dimensionality reduction using mixture models
Given a classification problem, our goal is to find a low-dimensional linear transformation of the feature vectors which retains information needed to predict the class labels. We...
Sajama, Alon Orlitsky
CVPR
2009
IEEE
14 years 1 months ago
"Who are you?" - Learning person specific classifiers from video
We investigate the problem of automatically labelling faces of characters in TV or movie material with their names, using only weak supervision from automaticallyaligned subtitle ...
Josef Sivic, Mark Everingham, Andrew Zisserman
CIKM
2008
Springer
13 years 11 months ago
Semi-supervised text categorization by active search
In automated text categorization, given a small number of labeled documents, it is very challenging, if not impossible, to build a reliable classifier that is able to achieve high...
Zenglin Xu, Rong Jin, Kaizhu Huang, Michael R. Lyu...