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» An Improved LAZY-AR Approach to Bayesian Network Inference
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FLAIRS
2004
15 years 7 months ago
Case-Based Bayesian Network Classifiers
We propose a new approach for learning Bayesian classifiers from data. Although it relies on traditional Bayesian network (BN) learning algorithms, the effectiveness of our approa...
Eugene Santos, Ahmed Huessin
BMCBI
2007
153views more  BMCBI 2007»
15 years 6 months ago
A new pairwise kernel for biological network inference with support vector machines
Background: Much recent work in bioinformatics has focused on the inference of various types of biological networks, representing gene regulation, metabolic processes, protein-pro...
Jean-Philippe Vert, Jian Qiu, William Stafford Nob...
BMCBI
2008
174views more  BMCBI 2008»
15 years 6 months ago
Evolutionary approaches for the reverse-engineering of gene regulatory networks: A study on a biologically realistic dataset
Background: Inferring gene regulatory networks from data requires the development of algorithms devoted to structure extraction. When only static data are available, gene interact...
Cédric Auliac, Vincent Frouin, Xavier Gidro...
UAI
2004
15 years 7 months ago
An Empirical Evaluation of Possible Variations of Lazy Propagation
As real-world Bayesian networks continue to grow larger and more complex, it is important to investigate the possibilities for improving the performance of existing algorithms of ...
Andres Madsen
CORR
2011
Springer
177views Education» more  CORR 2011»
15 years 1 months ago
Tuffy: Scaling up Statistical Inference in Markov Logic Networks using an RDBMS
Markov Logic Networks (MLNs) have emerged as a powerful framework that combines statistical and logical reasoning; they have been applied to many data intensive problems including...
Feng Niu, Christopher Ré, AnHai Doan, Jude ...