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ICCV
2007
IEEE
15 years 4 months ago
2007
IEEE
This paper treats tracking as a foreground/background classification problem and proposes an online semisupervised learning framework. Initialized with a small number of labeled ...
ICML
2006
IEEE
15 years 10 months ago
2006
IEEE
Semi-Supervised Support Vector Machines (S3 VMs) are an appealing method for using unlabeled data in classification: their objective function favors decision boundaries which do n...
73
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JMLR
2010
14 years 4 months ago
2010
This paper proposes a novel algorithm for semisupervised learning. This algorithm learns graph cuts that maximize the margin with respect to the labels induced by the harmonic fun...
76
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CVPR
2005
IEEE
15 years 11 months ago
2005
IEEE
Although recent studies have shown that unlabeled data are beneficial to boosting the image retrieval performance, very few approaches for image retrieval can learn with labeled a...
94
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ICML
2009
IEEE
15 years 10 months ago
2009
IEEE
Semi-Supervised Support Vector Machines (S3VMs) typically directly estimate the label assignments for the unlabeled instances. This is often inefficient even with recent advances ...