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AAAI
2007
13 years 7 months ago
Probabilistic Community Discovery Using Hierarchical Latent Gaussian Mixture Model
Complex networks exist in a wide array of diverse domains, ranging from biology, sociology, and computer science. These real-world networks, while disparate in nature, often compr...
Haizheng Zhang, C. Lee Giles, Henry C. Foley, John...
BMCBI
2010
158views more  BMCBI 2010»
13 years 5 months ago
A Bayesian network approach to feature selection in mass spectrometry data
Background: Time-of-flight mass spectrometry (TOF-MS) has the potential to provide non-invasive, high-throughput screening for cancers and other serious diseases via detection of ...
Karl W. Kuschner, Dariya I. Malyarenko, William E....
BMCBI
2007
153views more  BMCBI 2007»
13 years 5 months ago
Estimating genealogies from linked marker data: a Bayesian approach
Background: Answers to several fundamental questions in statistical genetics would ideally require knowledge of the ancestral pedigree and of the gene flow therein. A few examples...
Dario Gasbarra, Matti Pirinen, Mikko J. Sillanp&au...
MICAI
2007
Springer
13 years 11 months ago
Optimizing Inference in Bayesian Networks and Semiring Valuation Algebras
Previous work on context-specific independence in Bayesian networks is driven by a common goal, namely to represent the conditional probability tables in a most compact way. In th...
Michael Wachter, Rolf Haenni, Marc Pouly
UAI
2003
13 years 6 months ago
Learning Module Networks
Methods for learning Bayesian networks can discover dependency structure between observed variables. Although these methods are useful in many applications, they run into computat...
Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller,...