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» Maximal Margin Labeling for Multi-Topic Text Categorization
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NIPS
2004
13 years 5 months ago
Maximal Margin Labeling for Multi-Topic Text Categorization
Hideto Kazawa, Tomonori Izumitani, Hirotoshi Taira...
ICCV
2009
IEEE
14 years 9 months ago
Semi-Supervised Random Forests
Random Forests (RFs) have become commonplace in many computer vision applications. Their popularity is mainly driven by their high computational efficiency during both training ...
Christian Leistner, Amir Saffari, Jakob Santner, H...
ICML
2004
IEEE
14 years 5 months ago
Leveraging the margin more carefully
Boosting is a popular approach for building accurate classifiers. Despite the initial popular belief, boosting algorithms do exhibit overfitting and are sensitive to label noise. ...
Nir Krause, Yoram Singer
PKDD
2010
Springer
212views Data Mining» more  PKDD 2010»
13 years 2 months ago
Cross Validation Framework to Choose amongst Models and Datasets for Transfer Learning
Abstract. One solution to the lack of label problem is to exploit transfer learning, whereby one acquires knowledge from source-domains to improve the learning performance in the t...
ErHeng Zhong, Wei Fan, Qiang Yang, Olivier Versche...