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» On the Learnability of Vector Spaces
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WSCG
2003
174views more  WSCG 2003»
13 years 9 months ago
An Efficient Algorithm for Codebook Design in Transform Vector Quantization
In this paper, a new wavelet-domain codebook design algorithm is proposed for image coding. The method utilizes mean-squared error and variance based selection schemes for good cl...
Momotaz Begum, Nurun Nahar, Kaneez Fatimah, M. K. ...
DAM
2008
83views more  DAM 2008»
13 years 8 months ago
Multi-group support vector machines with measurement costs: A biobjective approach
Support Vector Machine has shown to have good performance in many practical classification settings. In this paper we propose, for multi-group classification, a biobjective optimi...
Emilio Carrizosa, Belen Martin-Barragan, Dolores R...
NN
2000
Springer
161views Neural Networks» more  NN 2000»
13 years 8 months ago
How good are support vector machines?
Support vector (SV) machines are useful tools to classify populations characterized by abrupt decreases in density functions. At least for one class of Gaussian data model the SV ...
Sarunas Raudys
SAC
2008
ACM
13 years 8 months ago
Towards automatic feature vector optimization for multimedia applications
We systematically evaluate a recently proposed method for unsupervised discrimination power analysis for feature selection and optimization in multimedia applications. A series of...
Tobias Schreck, Dieter W. Fellner, Daniel A. Keim
ICDM
2009
IEEE
200views Data Mining» more  ICDM 2009»
13 years 6 months ago
Improving SVM Classification on Imbalanced Data Sets in Distance Spaces
Abstract--Imbalanced data sets present a particular challenge to the data mining community. Often, it is the rare event that is of interest and the cost of misclassifying the rare ...
Suzan Koknar-Tezel, Longin Jan Latecki