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ICASSP
2009
IEEE
16 years 1 months ago
Microarray classification using block diagonal linear discriminant analysis with embedded feature selection
In this paper, block diagonal linear discriminant analysis (BDLDA) is improved and applied to gene expression data. BDLDA is a classification tool with embedded feature selection...
Lingyan Sheng, Roger Pique-Regi, Shahab Asgharzade...
IBPRIA
2003
Springer
15 years 11 months ago
Supervised Locally Linear Embedding Algorithm for Pattern Recognition
The dimensionality of the input data often far exceeds their intrinsic dimensionality. As a result, it may be difficult to recognize multidimensional data, especially if the number...
Olga Kouropteva, Oleg Okun, Matti Pietikäinen
FGR
2000
IEEE
181views Biometrics» more  FGR 2000»
15 years 10 months ago
Face Detection Using Mixtures of Linear Subspaces
We present two methods using mixtures of linear subspaces for face detection in gray level images. One method uses a mixture of factor analyzers to concurrently perform clustering...
Ming-Hsuan Yang, Narendra Ahuja, David J. Kriegman
ASPDAC
1999
ACM
93views Hardware» more  ASPDAC 1999»
15 years 10 months ago
Optimization of Linear Placements for Wirelength Minimization with Free Sites
We study a type of linear placement problem arising in detailed placement optimization of a given cell row in the presence of white-space (extra sites). In this single-row placeme...
Andrew B. Kahng, Paul Tucker, Alexander Zelikovsky
DAGM
2006
Springer
15 years 10 months ago
Linear vs. Nonlinear Feature Combination for Saliency Computation: A Comparison with Human Vision
In the heart of the computer model of visual attention, an interest or saliency map is derived from an input image in a process that encompasses several data combination steps. Whi...
Nabil Ouerhani, Alexandre Bur, Heinz Hügli