434 search results - page 12 / 87 » Dimensionality Reduction of Clustered Data Sets |
ICPP
2000
IEEE
14 years 29 days ago
2000
IEEE
Clustering is a data mining problem which finds dense regions in a sparse multi-dimensional data set. The attribute values and ranges of these regions characterize the clusters. ...
BMCBI
2010
13 years 8 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...
ICPR
2006
IEEE
14 years 9 months ago
2006
IEEE
1 A kernel determines the inductive bias of a learning algorithm on a specific data set, and it is beneficial to design specific kernel for a given data set. In this work, we propo...
ICRA
2005
IEEE
14 years 2 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...
ICML
2005
IEEE
14 years 9 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...