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ACML
2009
Springer
14 years 3 months ago
Linear Time Model Selection for Mixture of Heterogeneous Components
Abstract: Our main contribution is to propose a novel model selection methodology, expectation minimization of information criterion (EMIC). EMIC makes a significant impact on the...
Ryohei Fujimaki, Satoshi Morinaga, Michinari Momma...
CORR
2006
Springer
130views Education» more  CORR 2006»
13 years 9 months ago
Genetic Programming for Kernel-based Learning with Co-evolving Subsets Selection
Abstract. Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on the fact that i) linear learning can be formalized as a well-posed opti...
Christian Gagné, Marc Schoenauer, Mich&egra...
PRL
2006
79views more  PRL 2006»
13 years 9 months ago
Multi-class feature selection for texture classification
In this paper, a multi-class feature selection scheme based on recursive feature elimination (RFE) is proposed for texture classifications. The feature selection scheme is perform...
Xue-wen Chen, Xiang-Yan Zeng, Deborah van Alphen
COLING
2002
13 years 8 months ago
Efficient Support Vector Classifiers for Named Entity Recognition
Named Entity (NE) recognition is a task in which proper nouns and numerical information are extracted from documents and are classified into categories such as person, organizatio...
Hideki Isozaki, Hideto Kazawa
IVC
2006
259views more  IVC 2006»
13 years 9 months ago
Object detection using spatial histogram features
In this paper, we propose an object detection approach using spatial histogram features. As spatial histograms consist of marginal distributions of an image over local patches, th...
Hongming Zhang, Wen Gao, Xilin Chen, Debin Zhao