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» Parallel Support Vector Machines: The Cascade SVM
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CORR
2006
Springer
130views Education» more  CORR 2006»
13 years 8 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...
CIKM
2006
Springer
14 years 14 days ago
Coupling feature selection and machine learning methods for navigational query identification
It is important yet hard to identify navigational queries in Web search due to a lack of sufficient information in Web queries, which are typically very short. In this paper we st...
Yumao Lu, Fuchun Peng, Xin Li, Nawaaz Ahmed
CSL
2010
Springer
13 years 7 months ago
Voice activity detection based on statistical models and machine learning approaches
The voice activity detectors (VADs) based on statistical models have shown impressive performances especially when fairly precise statistical models are employed. Moreover, the ac...
Jong Won Shin, Joon-Hyuk Chang, Nam Soo Kim
ESWA
2008
151views more  ESWA 2008»
13 years 8 months ago
Automated diagnosis of sewer pipe defects based on machine learning approaches
In sewage rehabilitation planning, closed circuit television (CCTV) systems are the widely used inspection tools in assessing sewage structural conditions for non man entry pipes....
Ming-Der Yang, Tung-Ching Su
AVBPA
2005
Springer
226views Biometrics» more  AVBPA 2005»
14 years 2 months ago
Discriminant Analysis Based on Kernelized Decision Boundary for Face Recognition
A novel nonlinear discriminant analysis method, Kernelized Decision Boundary Analysis (KDBA), is proposed in our paper, whose Decision Boundary feature vectors are the normal vecto...
Baochang Zhang, Xilin Chen, Wen Gao