502 search results - page 15 / 101 » Principal Component Analysis for Sparse High-Dimensional Dat... |
ICPR
2004
IEEE
14 years 8 months ago
2004
IEEE
In a previous paper [1], we have presented a new linear classification algorithm, Principal Component Null Space Analysis (PCNSA) which is designed for problems like object recogn...
ECCV
2002
Springer
14 years 9 months ago
2002
Springer
Abstract. Principal Component Analysis (PCA) is one of the most popular techniques for dimensionality reduction of multivariate data points with application areas covering many bra...
IEEEARES
2006
IEEE
14 years 1 months ago
2006
IEEE
Most current anomaly Intrusion Detection Systems (IDSs) detect computer network behavior as normal or abnormal but cannot identify the type of attacks. Moreover, most current intr...
NPL
2006
13 years 7 months ago
2006
Abstract. In this paper we introduce a new error measure, integrated reconstruction error (IRE) and show that the minimization of IRE leads to principal eigenvectors (without rotat...
CVPR
2003
IEEE
14 years 9 months ago
2003
IEEE
This paper presents an algebro-geometric solution to the problem of segmenting an unknown number of subspaces of unknown and varying dimensions from sample data points. We represen...