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» Linear Laplacian Discrimination for Feature Extraction
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KES
2005
Springer
15 years 3 months ago
Feature Generation by Simple FLD
This paper presents a new algorithm for feature generation, which is approximately derived based on geometrical interpretation of the Fisher linear discriminant analysis. In a fiel...
Minoru Fukumi, Yasue Mitsukura
KDD
2006
ACM
179views Data Mining» more  KDD 2006»
15 years 10 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
ICASSP
2010
IEEE
14 years 10 months ago
Boosted binary features for noise-robust speaker verification
The standard approach to speaker verification is to extract cepstral features from the speech spectrum and model them by generative or discriminative techniques. We propose a nov...
Anindya Roy, Mathew Magimai-Doss, Sébastien...
ICPR
2008
IEEE
15 years 11 months ago
Kernel oriented discriminant analysis for speaker-independent phoneme spaces
Speaker independent feature extraction is a critical problem in speech recognition. Oriented principal component analysis (OPCA) is a potential solution that can find a subspace r...
Heeyoul Choi, Ricardo Gutierrez-Osuna, Seungjin Ch...
CVPR
2010
IEEE
15 years 2 months ago
Bayes Optimal Kernel Discriminant Analysis
Kernel methods provide an efficient mechanism to derive nonlinear algorithms. In classification problems as well as in feature extraction, kernel-based approaches map the original...
Di You, Aleix Martinez