159 search results - page 11 / 32 » Sparse non-Gaussian component analysis |
198
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JMLR
2012
13 years 8 months ago
2012
Traditional tensor decompositions such as the CANDECOMP / PARAFAC (CP) and Tucker decompositions yield higher-order principal components that have been used to understand tensor d...
160
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ICA
2007
Springer
15 years 9 months ago
2007
Springer
We propose a new method for estimating the mixing matrix, A, in the linear model x(t) = As(t), t = 1, . . . , T, for the problem of underdetermined Sparse Component Analysis (SCA)....
149
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ICONIP
2007
15 years 7 months ago
2007
In the paper, we present a new approach to multi-way Blind Source Separation (BSS) and corresponding 3D tensor factorization that has many potential applications in neuroscience an...
164
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ICONIP
2007
15 years 7 months ago
2007
Abstract. Principal component analysis (PCA) is a widely used technique for data analysis and dimensionality reduction. Eigenvalue decomposition is the standard algorithm for solvi...
184
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ICML
2007
IEEE
16 years 6 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...