1083 search results - page 15 / 217 » Robust principal component analysis |
JMLR
2012
11 years 10 months ago
2012
Traditional tensor decompositions such as the CANDECOMP / PARAFAC (CP) and Tucker decompositions yield higher-order principal components that have been used to understand tensor d...
ICIP
2005
IEEE
14 years 1 months ago
2005
IEEE
This paper presents a view independent face recognition method based on kernel principal component analysis (KPCA) of local parts. View changes induce large variation in feature s...
COLT
2004
Springer
14 years 28 days ago
2004
Springer
The main goal of this paper is to prove inequalities on the reconstruction error for Kernel Principal Component Analysis. With respect to previous work on this topic, our contribu...
ECML
2004
Springer
14 years 28 days ago
2004
Springer
This work presents a novel procedure for computing (1) distances between nodes of a weighted, undirected, graph, called the Euclidean Commute Time Distance (ECTD), and (2) a subspa...
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...