5131 search results - page 85 / 1027 » Heterogeneous Component Analysis |
ICML
2006
IEEE
14 years 11 months ago
2006
IEEE
Principal component analysis (PCA) minimizes the sum of squared errors (L2-norm) and is sensitive to the presence of outliers. We propose a rotational invariant L1-norm PCA (R1-PC...
ISBI
2006
IEEE
2006
IEEE
Mixture principal component analysis for distribution volume parametric imaging in brain PET studies
14 years 10 months ago
In this paper, we present a mixture Principal Component Analysis (mPCA)-based approach for voxel level quantification of dynamic positron emission tomography (PET) data in brain s...
ICML
2009
IEEE
14 years 4 months ago
2009
IEEE
One of the main problems in probabilistic grammatical inference consists in inferring a stochastic language, i.e. a probability distribution, in some class of probabilistic models...
GLOBECOM
2009
IEEE
14 years 4 months ago
2009
IEEE
—In this paper we look at the problem of accurately reconstructing distributed signals through the collection of a small number of samples at a data gathering point. The techniqu...
ICASSP
2008
IEEE
14 years 4 months ago
2008
IEEE
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...