140 search results - page 8 / 28 » Dimensionality Reduction with Adaptive Kernels |
WEBI
2010
Springer
13 years 5 months ago
2010
Springer
High-dimensional data usually incur learning deficiencies and computational difficulties. We present a novel semi-supervised dimensionality reduction technique that embeds high-dim...
BMCBI
2010
13 years 7 months ago
2010
Background: Recent advances in proteomics technologies such as SELDI-TOF mass spectrometry has shown promise in the detection of early stage cancers. However, dimensionality reduc...
CVPR
2008
IEEE
14 years 9 months ago
2008
IEEE
Nearest neighbour classifiers and related kernel methods often perform poorly in high dimensional problems because it is infeasible to include enough training samples to cover the...
ICIP
2005
IEEE
14 years 9 months ago
2005
IEEE
This article presents the use of morphological amoebas for the enhancement of 3D medical images. Morphological amoebas are kernels adapting their shape in such a way that they do ...
SPEECH
1998
13 years 7 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...