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» Graph model selection using maximum likelihood
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JMLR
2008
141views more  JMLR 2008»
13 years 7 months ago
Graphical Methods for Efficient Likelihood Inference in Gaussian Covariance Models
In graphical modelling, a bi-directed graph encodes marginal independences among random variables that are identified with the vertices of the graph. We show how to transform a bi...
Mathias Drton, Thomas S. Richardson
BMCBI
2010
178views more  BMCBI 2010»
13 years 7 months ago
Selecting high-dimensional mixed graphical models using minimal AIC or BIC forests
Background: Chow and Liu showed that the maximum likelihood tree for multivariate discrete distributions may be found using a maximum weight spanning tree algorithm, for example K...
David Edwards, Gabriel C. G. de Abreu, Rodrigo Lab...
TIT
2008
102views more  TIT 2008»
13 years 7 months ago
On Low-Complexity Maximum-Likelihood Decoding of Convolutional Codes
Abstract--This letter considers the average complexity of maximum-likelihood (ML) decoding of convolutional codes. ML decoding can be modeled as finding the most probable path take...
Jie Luo
BMCBI
2006
137views more  BMCBI 2006»
13 years 7 months ago
A maximum likelihood framework for protein design
Background: The aim of protein design is to predict amino-acid sequences compatible with a given target structure. Traditionally envisioned as a purely thermodynamic question, thi...
Claudia L. Kleinman, Nicolas Rodrigue, Céci...