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CORR
2010
Springer
171views Education» more  CORR 2010»
13 years 7 months ago
Solving Inverse Problems with Piecewise Linear Estimators: From Gaussian Mixture Models to Structured Sparsity
A general framework for solving image inverse problems is introduced in this paper. The approach is based on Gaussian mixture models, estimated via a computationally efficient MAP...
Guoshen Yu, Guillermo Sapiro, Stéphane Mall...
GECCO
2009
Springer
159views Optimization» more  GECCO 2009»
14 years 3 hour ago
Bayesian network structure learning using cooperative coevolution
We propose a cooperative-coevolution – Parisian trend – algorithm, IMPEA (Independence Model based Parisian EA), to the problem of Bayesian networks structure estimation. It i...
Olivier Barrière, Evelyne Lutton, Pierre-He...
GEOINFORMATICA
1998
107views more  GEOINFORMATICA 1998»
13 years 7 months ago
A Comparison of Two Approaches to Ranking Algorithms Used to Compute Hill Slopes
The calculation of slope (downhill gradient) for a point in a digital elevation model (DEM) is a common procedure in the hydrological, environmental and remote sensing sciences. T...
Kevin H. Jones
BMCBI
2010
181views more  BMCBI 2010»
13 years 7 months ago
Intensity dependent estimation of noise in microarrays improves detection of differentially expressed genes
Background: In many microarray experiments, analysis is severely hindered by a major difficulty: the small number of samples for which expression data has been measured. When one ...
Amit Zeisel, Amnon Amir, Wolfgang J. Köstler,...
CORR
2007
Springer
128views Education» more  CORR 2007»
13 years 7 months ago
Model Selection Through Sparse Maximum Likelihood Estimation
We consider the problem of estimating the parameters of a Gaussian or binary distribution in such a way that the resulting undirected graphical model is sparse. Our approach is to...
Onureena Banerjee, Laurent El Ghaoui, Alexandre d'...