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» Training Data Selection for Support Vector Machines
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CVPR
2008
IEEE
14 years 11 months ago
Margin-based discriminant dimensionality reduction for visual recognition
Nearest neighbour classifiers and related kernel methods often perform poorly in high dimensional problems because it is infeasible to include enough training samples to cover the...
Hakan Cevikalp, Bill Triggs, Frédéri...
COLT
2000
Springer
14 years 1 months ago
Model Selection and Error Estimation
We study model selection strategies based on penalized empirical loss minimization. We point out a tight relationship between error estimation and data-based complexity penalizatio...
Peter L. Bartlett, Stéphane Boucheron, G&aa...
CVPR
2010
IEEE
14 years 5 months ago
Rapid Selection of Reliable Templates for Visual Tracking
We propose a method that rates the suitability of given templates for template-based tracking in real-time. This is important for applications with online template selection, such...
Nicolas Alt, Stefan Hinterstoisser, Nassir Navab
BMCBI
2007
178views more  BMCBI 2007»
13 years 9 months ago
SVM clustering
Background: Support Vector Machines (SVMs) provide a powerful method for classification (supervised learning). Use of SVMs for clustering (unsupervised learning) is now being cons...
Stephen Winters-Hilt, Sam Merat
BMCBI
2008
134views more  BMCBI 2008»
13 years 9 months ago
Identification of transcription factor contexts in literature using machine learning approaches
Background: Availability of information about transcription factors (TFs) is crucial for genome biology, as TFs play a central role in the regulation of gene expression. While man...
Hui Yang, Goran Nenadic, John A. Keane