1731 search results - page 100 / 347 » Maximum likelihood analysis of algorithms and data structure... |
CORR
2010
Springer
13 years 7 months ago
2010
Springer
Learning structured representations has emerged as an important problem in many domains, including document and Web data mining, bioinformatics, and image analysis. One approach t...
NIPS
1998
13 years 9 months ago
1998
The Expectation Maximization EM algorithm is an iterative procedure for maximum likelihood parameter estimation from data sets with missing or hidden variables 2 . It has been app...
BMCBI
2008
13 years 8 months ago
2008
Background: Identification of differentially expressed genes is a typical objective when analyzing gene expression data. Recently, Bayesian hierarchical models have become increas...
IJAR
2010
13 years 6 months ago
2010
We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...
BMCBI
2010
13 years 8 months ago
2010
Background: The estimation of demographic parameters from genetic data often requires the computation of likelihoods. However, the likelihood function is computationally intractab...