166 search results - page 13 / 34 » Learning a kernel matrix for nonlinear dimensionality reduct... |
TIP
2011
13 years 3 months ago
2011
—This paper introduces kernel versions of maximum autocorrelation factor (MAF) analysis and minimum noise fraction (MNF) analysis. The kernel versions are based upon a dual formu...
SPEECH
1998
13 years 8 months ago
1998
We consider the problem of obtaining a reduced dimension representation of electropalatographic (EPG) data. An unsupervised learning approach based on latent variable modelling is...
BMVC
2010
13 years 6 months ago
2010
We present a framework for the reduction of dimensionality of a data set via manifold learning. Using the building blocks of local hyperplanes we show how a global manifold can be...
ICDM
2007
IEEE
13 years 10 months ago
2007
IEEE
An easily implementable mixed-integer algorithm is proposed that generates a nonlinear kernel support vector machine (SVM) classifier with reduced input space features. A single ...
COLT
2008
Springer
13 years 10 months ago
2008
Springer
A Hilbert space embedding for probability measures has recently been proposed, with applications including dimensionality reduction, homogeneity testing and independence testing. ...