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» The Inefficiency of Batch Training for Large Training Sets
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AINA
2004
IEEE
13 years 11 months ago
Online Training of SVMs for Real-time Intrusion Detection
Abstract-- As intrusion detection essentially can be formulated as a binary classification problem, it thus can be solved by an effective classification technique-Support Vector Ma...
Zonghua Zhang, Hong Shen
EMO
2009
Springer
147views Optimization» more  EMO 2009»
14 years 2 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...
PAMI
2008
139views more  PAMI 2008»
13 years 7 months ago
A Fast Algorithm for Learning a Ranking Function from Large-Scale Data Sets
We consider the problem of learning a ranking function that maximizes a generalization of the Wilcoxon-Mann-Whitney statistic on the training data. Relying on an -accurate approxim...
Vikas C. Raykar, Ramani Duraiswami, Balaji Krishna...
CVPR
2010
IEEE
14 years 3 months ago
Tag-based Web Photo Retrieval Improved by Batch Mode Re-Tagging
Web photos in social media sharing websites such as Flickr are generally accompanied by rich but noisy textual descriptions (tags, captions, categories, etc.). In this paper, we p...
Lin Chen, Dong Xu, Wai-Hung Tsang, Jiebo Luo
ANNPR
2008
Springer
13 years 9 months ago
Supervised Incremental Learning with the Fuzzy ARTMAP Neural Network
Abstract. Automatic pattern classifiers that allow for on-line incremental learning can adapt internal class models efficiently in response to new information without retraining fr...
Jean-François Connolly, Eric Granger, Rober...