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» Covering Numbers for Support Vector Machines
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MICCAI
2006
Springer
16 years 23 days ago
MR Image Segmentation Using Phase Information and a Novel Multiscale Scheme
This paper considers the problem of automatic classification of textured tissues in 3D MRI. More specifically, it aims at validating the use of features extracted from the phase of...
Jurgen Fripp, Peter Stanwell, Pierrick Bourgeat, S...
EMO
2009
Springer
147views Optimization» more  EMO 2009»
15 years 6 months ago
Application of MOGA Search Strategy to SVM Training Data Selection
When training Support Vector Machine (SVM), selection of a training data set becomes an important issue, since the problem of overfitting exists with a large number of training da...
Tomoyuki Hiroyasu, Masashi Nishioka, Mitsunori Mik...
IJCNN
2006
IEEE
15 years 5 months ago
Learning to Rank by Maximizing AUC with Linear Programming
— Area Under the ROC Curve (AUC) is often used to evaluate ranking performance in binary classification problems. Several researchers have approached AUC optimization by approxi...
Kaan Ataman, W. Nick Street, Yi Zhang
CIVR
2005
Springer
123views Image Analysis» more  CIVR 2005»
15 years 5 months ago
Region-Based Image Clustering and Retrieval Using Multiple Instance Learning
Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. We propose an approach based on One-Class Support ...
Chengcui Zhang, Xin Chen
MCS
2005
Springer
15 years 5 months ago
Ensemble of SVMs for Incremental Learning
Support Vector Machines (SVMs) have been successfully applied to solve a large number of classification and regression problems. However, SVMs suffer from the catastrophic forgetti...
Zeki Erdem, Robi Polikar, Fikret S. Gürgen, N...