58 search results - page 4 / 12 » A scalable supervised algorithm for dimensionality reduction... |
KDD
2006
ACM
14 years 9 months ago
2006
ACM
Principal component analysis (PCA) has been extensively applied in data mining, pattern recognition and information retrieval for unsupervised dimensionality reduction. When label...
ACL
2010
13 years 6 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 ...
ICML
2007
IEEE
14 years 9 months ago
2007
IEEE
In this paper we investigate the regularization property of Kernel Principal Component Analysis (KPCA), by studying its application as a preprocessing step to supervised learning ...
PAMI
2007
13 years 8 months ago
2007
—Over the past few decades, a large family of algorithms—supervised or unsupervised; stemming from statistics or geometry theory—has been designed to provide different soluti...
ICANN
2003
Springer
14 years 1 months ago
2003
Springer
Locally linear embedding (LLE) is a recently proposed method for unsupervised nonlinear dimensionality reduction. It has a number of attractive features: it does not require an ite...