119 search results - page 6 / 24 » Sparse kernel methods for high-dimensional survival data |
IJCAI
2007
13 years 8 months ago
2007
Kernel based nonlinear Feature Extraction (KFE) or dimensionality reduction is a widely used pre-processing step in pattern classification and data mining tasks. Given a positive...
IJON
2011
13 years 2 months ago
2011
Abstract. The generative topographic mapping (GTM) has been proposed as a statistical model to represent high dimensional data by means of a sparse lattice of points in latent spac...
NECO
2000
13 years 7 months ago
2000
We present a new method that we call Generalized Discriminant Analysis (GDA) to deal with nonlinear discriminant analysis using kernel function operator. The underlying theory is ...
SDM
2007
SIAM
13 years 8 months ago
2007
SIAM
In recent years, privacy preserving data mining has become very important because of the proliferation of large amounts of data on the internet. Many data sets are inherently high...
ICML
2004
IEEE
14 years 24 days ago
2004
IEEE
We investigate how to learn a kernel matrix for high dimensional data that lies on or near a low dimensional manifold. Noting that the kernel matrix implicitly maps the data into ...