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ICIP
2005
IEEE
16 years 8 months ago
A complementary SVMs-based image annotation system
A novel automatic image annotation system is proposed, which integrates two sets of SVMs (Support Vector Machines), namely the MIL-based (Multiple Instance Learning) and global-fe...
Yutao Han, Xiaojun Qi
EMO
2009
Springer
147views Optimization» more  EMO 2009»
16 years 1 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...
CVPR
2006
IEEE
15 years 10 months ago
Region-based Image Annotation using Asymmetrical Support Vector Machine-based Multiple-Instance Learning
In region-based image annotation, keywords are usually associated with images instead of individual regions in the training data set. This poses a major challenge for any learning...
Changbo Yang, Ming Dong, Jing Hua
ICML
2007
IEEE
16 years 7 months ago
Graph clustering with network structure indices
Graph clustering has become ubiquitous in the study of relational data sets. We examine two simple algorithms: a new graphical adaptation of the k-medoids algorithm and the Girvan...
Matthew J. Rattigan, Marc Maier, David Jensen
ICML
2005
IEEE
16 years 7 months ago
A martingale framework for concept change detection in time-varying data streams
In a data streaming setting, data points are observed one by one. The concepts to be learned from the data points may change infinitely often as the data is streaming. In this pap...
Shen-Shyang Ho