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AVBPA
2005
Springer
226views Biometrics» more  AVBPA 2005»
13 years 11 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
DOCENG
2003
ACM
13 years 11 months ago
Accuracy improvement of automatic text classification based on feature transformation
In this paper, we describe a comparative study on techniques of feature transformation and classification to improve the accuracy of automatic text classification. The normalizati...
Guowei Zu, Wataru Ohyama, Tetsushi Wakabayashi, Fu...
NIPS
2004
13 years 7 months ago
Efficient Kernel Discriminant Analysis via QR Decomposition
Linear Discriminant Analysis (LDA) is a well-known method for feature extraction and dimension reduction. It has been used widely in many applications such as face recognition. Re...
Tao Xiong, Jieping Ye, Qi Li, Ravi Janardan, Vladi...
PAMI
2007
217views more  PAMI 2007»
13 years 5 months ago
Discriminative Learning and Recognition of Image Set Classes Using Canonical Correlations
—We address the problem of comparing sets of images for object recognition, where the sets may represent variations in an object’s appearance due to changing camera pose and li...
Tae-Kyun Kim, Josef Kittler, Roberto Cipolla
KDD
2006
ACM
179views Data Mining» more  KDD 2006»
14 years 6 months ago
Extracting key-substring-group features for text classification
In many text classification applications, it is appealing to take every document as a string of characters rather than a bag of words. Previous research studies in this area mostl...
Dell Zhang, Wee Sun Lee