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ICPR
2004
IEEE
16 years 2 months ago
Classification Probability Analysis of Principal Component Null Space Analysis
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...
Namrata Vaswani, Rama Chellappa
ICANN
1997
Springer
15 years 6 months ago
Kernel Principal Component Analysis
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...
Bernhard Schölkopf, Alex J. Smola, Klaus-Robe...
101
Voted
EACL
2006
ACL Anthology
15 years 3 months ago
Improving Probabilistic Latent Semantic Analysis with Principal Component Analysis
Probabilistic Latent Semantic Analysis (PLSA) models have been shown to provide a better model for capturing polysemy and synonymy than Latent Semantic Analysis (LSA). However, th...
Ayman Farahat, Francine Chen
TIT
2002
72views more  TIT 2002»
15 years 1 months ago
Principal curves with bounded turn
Principal curves, like principal components, are a tool used in multivariate analysis for ends like feature extraction. Defined in their original form, principal curves need not ex...
S. Sandilya, Sanjeev R. Kulkarni
WEBI
2005
Springer
15 years 7 months ago
HITS is Principal Components Analysis
In this work, we show that Kleinberg’s hubs and authorities model (HITS) is simply Principal Components Analysis (PCA; maybe the most widely used multivariate statistical analys...
Marco Saerens, François Fouss