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Bayesian networks are probabilistic graphical models with a wide range of application areas including gene regulatory networks inference, risk analysis and image processing.
Estimating the dimension of a model
Gideon Schwarz · 1978
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Theory refinement on bayesian networks
Wray Buntine · 1991
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Using new data to refine a bayesian network
Wai Lam and Fahiem Bacchus · 1994
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Learning bayesian networks is NP-Complete
David Maxwell Chickering · 1995
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Learning bayesian networks: The combination of knowledge and statistical data
David Heckerman, Dan Geiger, and David M Chickering · 1995
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Combinatorial optimization: algorithms and complexity
Christos H Papadimitriou and Kenneth Steiglitz · 1998
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SAT vs CSP
Toby Walsh · 2000
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Preferred explanations and relaxations for over-constrained problems
Ulrich Junker · 2004
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Handbook of constraint programming
Francesca Rossi, Peter Van Beek, and Toby Walsh · 2006
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A simple approach for finding the globally optimal bayesian network structure
Tomi Silander and Petri Myllymäki · 2006
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Soft arc consistency revisited
Martin C Cooper, Simon de Givry, Martı Sánchez, Thomas Schiex, Matthias Zytnicki, and Tomas Werner · 2010
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Properties of bayesian dirichlet scores to learn bayesian network structures
Cassio Polpo de Campos and Qiang Ji · 2010
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Iterative and core-guided MaxSAT solving: A survey and assessment
António Morgado, Federico Heras, Mark H. Liffiton, Jordi Planes, and João Marques-Silva · 2013
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Learning optimal bayesian networks: A shortest path perspective
An improved lower bound for bayesian network structure learning
Xiannian Fan and Changhe Yuan · 2015
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Learning bayesian networks with thousands of variables
Mauro Scanagatta, Cassio P de Campos, Giorgio Corani, and Marco Zaffalon · 2015
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Machine learning of bayesian networks using constraint programming
Peter van Beek and Hella-Franziska Hoffmann · 2015
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Integer linear programming for the bayesian network structure learning problem
Mark Bartlett and James Cussens · 2017
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Bayesian network structure learning with integer programming: Polytopes, facets and complexity
James Cussens, Matti Järvisalo, Janne H Korhonen, and Mark Bartlett · 2017
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An experimental analysis of anytime algorithms for bayesian network structure learning
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Changhe Yuan and Brandon Malone · 2013
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Learning optimal bounded treewidth bayesian networks via maximum satisfiability
Jeremias Berg, Matti Järvisalo, and Brandon Malone · 2014
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Nearly-linear time positive LP solver with faster convergence rate
Zeyuan Allen-Zhu and Lorenzo Orecchia · 2015
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Colin Lee and Peter van Beek · 2017
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Entropy-based pruning for learning bayesian networks using BIC
Cassio P de Campos, Mauro Scanagatta, Giorgio Corani, and Marco Zaffalon · 2018
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Reasoning about inconsistent formulas
João Marques-Silva and Carlos Mencía · 2020
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