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» Margin based feature selection - theory and algorithms
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EMNLP
2009
13 years 5 months ago
Reverse Engineering of Tree Kernel Feature Spaces
We present a framework to extract the most important features (tree fragments) from a Tree Kernel (TK) space according to their importance in the target kernelbased machine, e.g. ...
Daniele Pighin, Alessandro Moschitti
ICCTA
2007
IEEE
13 years 7 months ago
Digital Signal Types Identification Using a Hierarchical SVM-Based Classifier and Efficient Features
Automatic digital signal type identification (ADSTI) is an important topic for both military and civilian communication applications. Most of proposed techniques (identifiers) can...
Ataollah Ebrahimzadeh, Seyed Alireza Seyedin
ICASSP
2009
IEEE
14 years 2 months ago
Maximizing global entropy reduction for active learning in speech recognition
We propose a new active learning algorithm to address the problem of selecting a limited subset of utterances for transcribing from a large amount of unlabeled utterances so that ...
Balakrishnan Varadarajan, Dong Yu, Li Deng, Alex A...

Publication
352views
13 years 1 months ago
A Contourlet Transform Feature Extraction Scheme for Ultrasound Thyroid Texture Classification
Ultrasonography is an invaluable and widely used medical imaging tool. Nevertheless, automatic texture analysis on ultrasound images remains a challenging issue. This work presen...
Stamos Katsigiannis, Eystratios G. Keramidas, Dimi...
ICANN
2007
Springer
13 years 11 months ago
Active Learning to Support the Generation of Meta-examples
Meta-Learning has been used to select algorithms based on the features of the problems being tackled. Each training example in this context, i.e. each meta-example, stores the feat...
Ricardo Bastos Cavalcante Prudêncio, Teresa ...