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ICNC
2005
Springer
14 years 1 months ago
An Incremental Learning Method Based on SVM for Online Sketchy Shape Recognition
This paper presents briefly an incremental learning method based on SVM for online sketchy shape recognition. It can collect all classified results corrected by user and select som...
Zhengxing Sun, Lisha Zhang, Enyi Tang
JMLR
2010
161views more  JMLR 2010»
13 years 2 months ago
Accuracy-Rejection Curves (ARCs) for Comparing Classification Methods with a Reject Option
Data extracted from microarrays are now considered an important source of knowledge about various diseases. Several studies based on microarray data and the use of receiver operat...
Malik Sajjad Ahmed Nadeem, Jean-Daniel Zucker, Bla...
ECML
2007
Springer
13 years 11 months ago
On Pairwise Naive Bayes Classifiers
Class binarizations are effective methods for improving weak learners by decomposing multi-class problems into several two-class problems. This paper analyzes how these methods can...
Jan-Nikolas Sulzmann, Johannes Fürnkranz, Eyk...
ICASSP
2008
IEEE
14 years 2 months ago
Ratio semi-definite classifiers
We present a novel classification model that is formulated as a ratio of semi-definite polynomials. We derive an efficient learning algorithm for this classifier, and apply it...
Jonathan Malkin, Jeff Bilmes
CVPR
2007
IEEE
14 years 9 months ago
Joint Optimization of Cascaded Classifiers for Computer Aided Detection
The existing methods for offline training of cascade classifiers take a greedy search to optimize individual classifiers in the cascade, leading inefficient overall performance. W...
Murat Dundar, Jinbo Bi