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CVPR
2008
IEEE
14 years 9 months ago
Mining compositional features for boosting
The selection of weak classifiers is critical to the success of boosting techniques. Poor weak classifiers do not perform better than random guess, thus cannot help decrease the t...
Junsong Yuan, Jiebo Luo, Ying Wu
SDM
2008
SIAM
256views Data Mining» more  SDM 2008»
13 years 9 months ago
Graph Mining with Variational Dirichlet Process Mixture Models
Graph data such as chemical compounds and XML documents are getting more common in many application domains. A main difficulty of graph data processing lies in the intrinsic high ...
Koji Tsuda, Kenichi Kurihara
BMCBI
2004
114views more  BMCBI 2004»
13 years 7 months ago
Profiled support vector machines for antisense oligonucleotide efficacy prediction
Background: This paper presents the use of Support Vector Machines (SVMs) for prediction and analysis of antisense oligonucleotide (AO) efficacy. The collected database comprises ...
Gustavo Camps-Valls, Alistair M. Chalk, Antonio J....
ICPR
2006
IEEE
14 years 8 months ago
Face Recognition by Combining Kernel Associative Memory and Gabor Transforms
Kernel associative memory (KAM) has previously been proposed as an efficient scheme for face recognition. In this paper, a hybrid method of combining KAM and Gabor wavelet transfo...
Bailing Zhang, Clement Leung, Yongsheng Gao
CVPR
2006
IEEE
14 years 9 months ago
On-line Boosting and Vision
Boosting has become very popular in computer vision, showing impressive performance in detection and recognition tasks. Mainly off-line training methods have been used, which impl...
Helmut Grabner, Horst Bischof