375 search results - page 64 / 75 » Bayesian Inference for Sparse Generalized Linear Models |
137
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MIAR
2006
IEEE
15 years 10 months ago
2006
IEEE
Segmentation of CSF and pulsative blood flow, based on a single phase contrast MRA (PC-MRA) image can lead to imperfect classifications. In this paper, we present a novel automated...
140
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NIPS
2008
15 years 5 months ago
2008
Kernel Principal Component Analysis (KPCA) is a popular generalization of linear PCA that allows non-linear feature extraction. In KPCA, data in the input space is mapped to highe...
199
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SIAMJO
2011
14 years 7 months ago
2011
Suppose we are given a matrix that is formed by adding an unknown sparse matrix to an unknown low-rank matrix. Our goal is to decompose the given matrix into its sparse and low-ran...
175
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JELIA
1994
Springer
15 years 8 months ago
1994
Springer
: In this paper we describe a general way of formalizing reasoning behaviour. Such a behaviour may be described by all the patterns which are valid for the behaviour. A pattern can...
129
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CORR
2010
Springer
15 years 4 months ago
2010
Springer
High-dimensional statistical inference deals with models in which the the number of parameters p is comparable to or larger than the sample size n. Since it is usually impossible ...