1083 search results - page 34 / 217 » Robust principal component analysis |
PR
2006
13 years 7 months ago
2006
In the past few years, some nonlinear dimensionality reduction (NLDR) or nonlinear manifold learning methods have aroused a great deal of interest in the machine learning communit...
NIPS
2003
13 years 9 months ago
2003
Principal components analysis (PCA) is one of the most widely used techniques in machine learning and data mining. Minor components analysis (MCA) is less well known, but can also...
FGR
2004
IEEE
13 years 11 months ago
2004
IEEE
Intra-personal space modeling proposed by Moghaddam et. al. has been successfully applied in face recognition. In their work the regular principal subspaces are derived from the i...
CORR
2000
Springer
13 years 7 months ago
2000
Springer
Analyzing the effect of concentrated noise on a typical decision-making process of a simplified two-candidate voting model, we have demonstrated that a local approach using a regi...
IDEAL
2003
Springer
14 years 25 days ago
2003
Springer
Abstract. Multidimensional data projection and visualisation are becoming increasingly important and have found wide applications in many fields such as decision support, bioinform...