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CORR
2010
Springer
320views Education» more  CORR 2010»
13 years 7 months ago
An algorithm for the principal component analysis of large data sets
Recently popularized randomized methods for principal component analysis (PCA) efficiently and reliably produce nearly optimal accuracy -- even on parallel processors -- unlike the...
Nathan Halko, Per-Gunnar Martinsson, Yoel Shkolnis...
ICCV
1999
IEEE
14 years 9 months ago
Independent Component Analysis of Textures
The technique of independent component analysis (ICA) is applied for texture feature detection. In ICA an optimal transformation (with respect to the statistical structure of the i...
Roberto Manduchi, Javier Portilla
ICASSP
2011
IEEE
12 years 11 months ago
Video thumbnail extraction using video time density function and independent component analysis mixture model
In this paper, we propose a new vector quantization method to create video thumbnail. In particular, we employ video time density function (VTDF) to explore the temporal character...
Junfeng Jiang, Xiao-Ping Zhang
ICML
2007
IEEE
14 years 8 months ago
Full regularization path for sparse principal component analysis
Given a sample covariance matrix, we examine the problem of maximizing the variance explained by a particular linear combination of the input variables while constraining the numb...
Alexandre d'Aspremont, Francis R. Bach, Laurent El...
ICASSP
2008
IEEE
14 years 1 months ago
Contextually adaptive signal representation using conditional principal component analysis
The conventional method of generating a basis that is optimally adapted (in MSE) for representation of an ensemble of signals is Principal Component Analysis (PCA). A more ambitio...
Rosa M. Figueras i Ventura, Umesh Rajashekar, Zhou...