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ICPR
2008
IEEE
15 years 4 months ago
Improving Bayesian Network parameter learning using constraints
This paper describes a new approach to unify constraints on parameters with training data to perform parameter estimation in Bayesian networks of known structure. The method is ge...
Cassio Polpo de Campos, Qiang Ji
JMLR
2012
13 years 2 days ago
Age-Layered Expectation Maximization for Parameter Learning in Bayesian Networks
The expectation maximization (EM) algorithm is a popular algorithm for parameter estimation in models with hidden variables. However, the algorithm has several non-trivial limitat...
Avneesh Singh Saluja, Priya Krishnan Sundararajan,...
BMCBI
2006
141views more  BMCBI 2006»
14 years 9 months ago
Visual setup of logical models of signaling and regulatory networks with ProMoT
Background: The analysis of biochemical networks using a logical (Boolean) description is an important approach in Systems Biology. Recently, new methods have been proposed to ana...
Julio Saez-Rodriguez, Sebastian Mirschel, Rebecca ...
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IJCNN
2006
IEEE
15 years 3 months ago
Implementing Synaptic Plasticity in a VLSI Spiking Neural Network Model
— This paper describes an area-efficient mixed-signal implementation of synapse-based long term plasticity realized in a VLSI1 model of a spiking neural network. The artificial...
Johannes Schemmel, Andreas Grübl, Karlheinz M...
BMCBI
2007
158views more  BMCBI 2007»
14 years 9 months ago
Penalized likelihood for sparse contingency tables with an application to full-length cDNA libraries
Background: The joint analysis of several categorical variables is a common task in many areas of biology, and is becoming central to systems biology investigations whose goal is ...
Corinne Dahinden, Giovanni Parmigiani, Mark C. Eme...