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» A continuation method for semi-supervised SVMs
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ICML
2006
IEEE
14 years 5 months ago
A continuation method for semi-supervised SVMs
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...
Olivier Chapelle, Mingmin Chi, Alexander Zien
ICCV
2007
IEEE
13 years 11 months ago
Co-Tracking Using Semi-Supervised Support Vector Machines
This paper treats tracking as a foreground/background classification problem and proposes an online semisupervised learning framework. Initialized with a small number of labeled ...
Feng Tang, Shane Brennan, Qi Zhao, Hai Tao
AAAI
2012
11 years 7 months ago
Semi-Supervised Kernel Matching for Domain Adaptation
In this paper, we propose a semi-supervised kernel matching method to address domain adaptation problems where the source distribution substantially differs from the target distri...
Min Xiao, Yuhong Guo
NAACL
2007
13 years 6 months ago
Semi-Supervised Learning for Semantic Parsing using Support Vector Machines
We present a method for utilizing unannotated sentences to improve a semantic parser which maps natural language (NL) sentences into their formal meaning representations (MRs). Gi...
Rohit J. Kate, Raymond J. Mooney
ICASSP
2008
IEEE
13 years 11 months ago
Nested support vector machines
The one-class and cost-sensitive support vector machines (SVMs) are state-of-the-art machine learning methods for estimating density level sets and solving weighted classificatio...
Gyemin Lee, Clayton Scott