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» Network bargaining: algorithms and structural results
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AUSAI
2006
Springer
13 years 11 months ago
Learning Hybrid Bayesian Networks by MML
Abstract. We use a Markov Chain Monte Carlo (MCMC) MML algorithm to learn hybrid Bayesian networks from observational data. Hybrid networks represent local structure, using conditi...
Rodney T. O'Donnell, Lloyd Allison, Kevin B. Korb
BMCBI
2008
142views more  BMCBI 2008»
13 years 8 months ago
Microarray data mining: A novel optimization-based approach to uncover biologically coherent structures
Background: DNA microarray technology allows for the measurement of genome-wide expression patterns. Within the resultant mass of data lies the problem of analyzing and presenting...
Meng Piao Tan, Erin N. Smith, James R. Broach, Chr...
GECCO
2004
Springer
134views Optimization» more  GECCO 2004»
14 years 1 months ago
A Descriptive Encoding Language for Evolving Modular Neural Networks
Evolutionary algorithms are a promising approach for the automated design of artificial neural networks, but they require a compact and efficient genetic encoding scheme to repres...
Jae-Yoon Jung, James A. Reggia
CIAC
2010
Springer
232views Algorithms» more  CIAC 2010»
13 years 11 months ago
Multicut Algorithms via Tree Decompositions
Various forms of multicut problems are of great importance in the area of network design. In general, these problems are intractable. However, several parameters have been identifi...
Reinhard Pichler, Stefan Rümmele, Stefan Woltran
ECML
1997
Springer
14 years 6 days ago
Parallel and Distributed Search for Structure in Multivariate Time Series
Abstract. E cient data mining algorithms are crucial fore ective knowledge discovery. We present the Multi-Stream Dependency Detection (msdd) data mining algorithm that performs a ...
Tim Oates, Matthew D. Schmill, Paul R. Cohen