166 search results - page 8 / 34 » Learning a kernel matrix for nonlinear dimensionality reduct... |
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
Many unsupervised algorithms for nonlinear dimensionality reduction, such as locally linear embedding (LLE) and Laplacian eigenmaps, are derived from the spectral decompositions o...
ICDM
2003
IEEE
14 years 23 days ago
2003
IEEE
We study the use of kernel subspace methods for learning low-dimensional representations for classification. We propose a kernel pooled local discriminant subspace method and com...
GPB
2010
13 years 4 months ago
2010
The detection of genes that show similar profiles under different experimental conditions is often an initial step in inferring the biological significance of such genes. Visualiz...
ESANN
2007
13 years 9 months ago
2007
We study dimensionality reduction or feature selection in text document categorization problem. We focus on the first step in building text categorization systems, that is the cho...
ICML
2007
IEEE
14 years 8 months ago
2007
IEEE
In this paper we investigate the regularization property of Kernel Principal Component Analysis (KPCA), by studying its application as a preprocessing step to supervised learning ...