93 search results - page 1 / 19 » Greedy Kernel Principal Component Analysis |
DAGSTUHL
2006
13 years 6 months ago
2006
ICDM
2006
IEEE
13 years 10 months ago
2006
IEEE
Choosing an appropriate kernel is one of the key problems in kernel-based methods. Most existing kernel selection methods require that the class labels of the training examples ar...
COLT
2004
Springer
13 years 10 months 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...
ICANN
1997
Springer
13 years 8 months ago
1997
Springer
A new method for performing a nonlinear form of Principal Component Analysis is proposed. By the use of integral operator kernel functions, one can e ciently compute principal comp...
IGARSS
2009
13 years 2 months ago
2009
Kernel Principal Component Analysis (KPCA) is investigated for feature extraction from hyperspectral remotesensing data. Features extracted using KPCA are used to construct the Ex...