847 search results - page 16 / 170 » HITS is Principal Components Analysis |
112
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ICML
2007
IEEE
16 years 1 months ago
2007
IEEE
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...
113
Voted
ISBI
2006
IEEE
2006
IEEE
Mixture principal component analysis for distribution volume parametric imaging in brain PET studies
16 years 1 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...
110
Voted
ICML
2009
IEEE
15 years 7 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...
106
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GLOBECOM
2009
IEEE
15 years 7 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
15 years 6 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...