92 search results - page 4 / 19 » Data Visualization and Dimensionality Reduction Using Kernel... |
ICML
2004
IEEE
14 years 7 months ago
2004
IEEE
Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...
ICRA
2005
IEEE
13 years 12 months ago
2005
IEEE
— The recent progress in robot mapping (or SLAM) algorithms has focused on estimating either point features (such as landmarks) or grid-based representations. Both of these repre...
EUROCAST
2003
Springer
13 years 11 months ago
2003
Springer
We propose a novel post processing method for visualization of fiber traces from DT-MRI data. Using a recently proposed non-linear dimensionality reduction technique, Laplacian ei...
VLDB
2000
ACM
13 years 10 months ago
2000
ACM
Many emerging application domains require database systems to support efficient access over highly multidimensional datasets. The current state-of-the-art technique to indexing hi...
PKDD
2010
Springer
13 years 4 months ago
2010
Springer
The foremost nonlinear dimensionality reduction algorithms provide an embedding only for the given training data, with no straightforward extension for test points. This shortcomin...