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KDD
2006
ACM
115views Data Mining» more  KDD 2006»
15 years 10 months ago
Supervised probabilistic principal component analysis
Principal component analysis (PCA) has been extensively applied in data mining, pattern recognition and information retrieval for unsupervised dimensionality reduction. When label...
Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Krieg...
NIPS
2008
14 years 11 months ago
Sparse probabilistic projections
We present a generative model for performing sparse probabilistic projections, which includes sparse principal component analysis and sparse canonical correlation analysis as spec...
Cédric Archambeau, Francis Bach
NIPS
2007
14 years 11 months ago
Predicting Brain States from fMRI Data: Incremental Functional Principal Component Regression
We propose a method for reconstruction of human brain states directly from functional neuroimaging data. The method extends the traditional multivariate regression analysis of dis...
Sennay Ghebreab, Arnold W. M. Smeulders, Pieter W....
ISBI
2011
IEEE
14 years 1 months ago
Principal components regression: Multivariate, gene-based tests in imaging genomics
In imaging genomics, there have been rapid advances in genome-wide, image-wide searches for genes that influence brain structure. Most efforts focus on univariate tests that treat...
Derrek P. Hibar, Jason L. Stein, Omid Kohannim, Ne...
IJCNN
2006
IEEE
15 years 3 months ago
Generalizing Independent Component Analysis for Two Related Data Sets
— We introduce in this paper methods for finding mutually corresponding dependent components from two different but related data sets in an unsupervised (blind) manner. The basi...
Juha Karhunen, Tomas Ukkonen