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» On learning algorithm selection for classification
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CVPR
2008
IEEE
15 years 8 months ago
Improving local learning for object categorization by exploring the effects of ranking
Local learning for classification is useful in dealing with various vision problems. One key factor for such approaches to be effective is to find good neighbors for the learning ...
Tien-Lung Chang, Tyng-Luh Liu, Jen-Hui Chuang
ECAI
2006
Springer
15 years 10 months ago
A Learning Classifier Approach to Tomography
Tomography is an important technique for noninvasive imaging: images of the interior of an object are computed from several scanned projections of the object, covering a range of a...
Kees Joost Batenburg
AI
2002
Springer
15 years 6 months ago
Learning cost-sensitive active classifiers
Most classification algorithms are "passive", in that they assign a class label to each instance based only on the description given, even if that description is incompl...
Russell Greiner, Adam J. Grove, Dan Roth
ICDM
2010
IEEE
226views Data Mining» more  ICDM 2010»
15 years 4 months ago
Edge Weight Regularization over Multiple Graphs for Similarity Learning
The growth of the web has directly influenced the increase in the availability of relational data. One of the key problems in mining such data is computing the similarity between o...
Pradeep Muthukrishnan, Dragomir R. Radev, Qiaozhu ...
SADM
2010
173views more  SADM 2010»
15 years 1 months ago
Data reduction in classification: A simulated annealing based projection method
This paper is concerned with classifying high dimensional data into one of two categories. In various settings, such as when dealing with fMRI and microarray data, the number of v...
Tian Siva Tian, Rand R. Wilcox, Gareth M. James