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» Bayesian Inference for Sparse Generalized Linear Models
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ICML
2009
IEEE
16 years 15 days ago
Nonparametric factor analysis with beta process priors
We propose a nonparametric extension to the factor analysis problem using a beta process prior. This beta process factor analysis (BPFA) model allows for a dataset to be decompose...
John William Paisley, Lawrence Carin
ICASSP
2011
IEEE
14 years 3 months ago
A general Bayesian algorithm for visual object tracking based on sparse features
This paper describes a Bayesian algorithm for rigid/non-rigid 2D visual object tracking based on sparse image features. The algorithm is inspired by the way human visual cortex se...
Mauricio Soto Alvarez, Carlo S. Regazzoni
CORR
2010
Springer
93views Education» more  CORR 2010»
14 years 11 months ago
On MMSE and MAP Denoising Under Sparse Representation Modeling Over a Unitary Dictionary
Among the many ways to model signals, a recent approach that draws considerable attention is sparse representation modeling. In this model, the signal is assumed to be generated a...
Javier Turek, Irad Yavneh, Matan Protter, Michael ...
AUSAI
2005
Springer
15 years 5 months ago
Conditioning Graphs: Practical Structures for Inference in Bayesian Networks
Abstract. Programmers employing inference in Bayesian networks typically rely on the inclusion of the model as well as an inference engine into their application. Sophisticated inf...
Kevin Grant, Michael C. Horsch