134 search results - page 14 / 27 » Random Projections for Manifold Learning |
CVPR
2005
IEEE
14 years 12 months ago
2005
IEEE
In [1], three popular subspace face recognition methods, PCA, Bayes, and LDA were analyzed under the same framework and an unified subspace analysis was proposed. However, since t...
Publication
This paper studies the effect of covariance regularization for classific ation of high-dimensional data. This is done by fitting a mixture of Gaussians with a regularized covaria...
KDD
2007
ACM
14 years 10 months ago
2007
ACM
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
NIPS
2007
13 years 11 months ago
2007
This paper investigates the application of randomized algorithms for large scale SVM learning. The key contribution of the paper is to show that, by using ideas random projections...
PKDD
2009
Springer
14 years 4 months ago
2009
Springer
Most existing semi-supervised learning methods are based on the smoothness assumption that data points in the same high density region should have the same label. This assumption, ...