73 search results - page 3 / 15 » Sparse Unsupervised Dimensionality Reduction Algorithms |
PAMI
2006
13 years 7 months ago
2006
Understanding the structure of multidimensional patterns, especially in unsupervised case, is of fundamental importance in data mining, pattern recognition and machine learning. Se...
PAMI
2008
13 years 7 months ago
2008
We present a novel probabilistic latent variable model to perform linear dimensionality reduction on data sets which contain clusters. We prove that the maximum likelihood solution...
PAMI
2007
13 years 7 months ago
2007
—A new unsupervised forward orthogonal search (FOS) algorithm is introduced for feature selection and ranking. In the new algorithm, features are selected in a stepwise way, one ...
ICONIP
2004
13 years 9 months ago
2004
Algorithms for nonlinear dimensionality reduction (NLDR) find meaningful hidden low-dimensional structures in a high-dimensional space. Current algorithms for NLDR are Isomaps, Loc...
ACL
2010
13 years 5 months ago
2010
We initiate a study comparing effectiveness of the transformed spaces learned by recently proposed supervised, and semisupervised metric learning algorithms to those generated by ...