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ICASSP
2009
IEEE
14 years 2 months ago
Voronoi cell shaping for feature selection with discrete HMMs
In this paper, we introduce a novel vector quantization (VQ) scheme for distributing the quantization error equally among the quantized dimensions. Afterwards, the proposed VQ sch...
Joachim Schenk, Gerhard Rigoll
CIVR
2004
Springer
189views Image Analysis» more  CIVR 2004»
14 years 29 days ago
Feature Based Cut Detection with Automatic Threshold Selection
There has been much work concentrated on creating accurate shot boundary detection algorithms in recent years. However a truly accurate method of cut detection still eludes researc...
Anthony Whitehead, Prosenjit Bose, Robert Lagani&e...
KDD
2009
ACM
180views Data Mining» more  KDD 2009»
14 years 8 months ago
Consensus group stable feature selection
Stability is an important yet under-addressed issue in feature selection from high-dimensional and small sample data. In this paper, we show that stability of feature selection ha...
Steven Loscalzo, Lei Yu, Chris H. Q. Ding
KDD
2005
ACM
205views Data Mining» more  KDD 2005»
14 years 1 months ago
Feature bagging for outlier detection
Outlier detection has recently become an important problem in many industrial and financial applications. In this paper, a novel feature bagging approach for detecting outliers in...
Aleksandar Lazarevic, Vipin Kumar
ICPR
2008
IEEE
14 years 8 months ago
A method of feature selection using contribution ratio based on boosting
AdaBoost and support vector machines (SVM) algorithms are commonly used in the field of object recognition. As classifiers, their classification performance is sensitive to affect...
Masamitsu Tsuchiya, Hironobu Fujiyoshi