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Learning Bayesian Networks: The Combination of Knowledge and Statistical
  Data

Learning Bayesian Networks: The Combination of Knowledge and Statistical Data

27 February 2013
David Heckerman
D. Geiger
D. M. Chickering
    TPM
ArXivPDFHTML

Papers citing "Learning Bayesian Networks: The Combination of Knowledge and Statistical Data"

16 / 366 papers shown
Title
On Identifying Significant Edges in Graphical Models of Molecular
  Networks
On Identifying Significant Edges in Graphical Models of Molecular Networks
M. Scutari
R. Nagarajan
60
167
0
05 Apr 2011
Bayes factors and the geometry of discrete hierarchical loglinear models
Bayes factors and the geometry of discrete hierarchical loglinear models
G. Letac
H. Massam
48
16
0
28 Mar 2011
Bayesian Network Structure Learning with Permutation Tests
Bayesian Network Structure Learning with Permutation Tests
M. Scutari
A. Brogini
55
25
0
27 Jan 2011
Efficient Independence-Based MAP Approach for Robust Markov Networks
  Structure Discovery
Efficient Independence-Based MAP Approach for Robust Markov Networks Structure Discovery
F. Bromberg
F. Schlüter
42
3
0
18 Jan 2011
An asymptotic approximation of the marginal likelihood for general
  Markov models
An asymptotic approximation of the marginal likelihood for general Markov models
Piotr Zwiernik
57
4
0
03 Dec 2010
A Probabilistic Approach for Learning Folksonomies from Structured Data
A Probabilistic Approach for Learning Folksonomies from Structured Data
Anon Plangprasopchok
Kristina Lerman
Lise Getoor
53
17
0
16 Nov 2010
A Brief Introduction to Temporality and Causality
A Brief Introduction to Temporality and Causality
K. Karimi
CML
60
9
0
14 Jul 2010
An Algorithm for Learning the Essential Graph
An Algorithm for Learning the Essential Graph
J. Noble
57
0
0
14 Jul 2010
Introduction to Graphical Modelling
Introduction to Graphical Modelling
M. Scutari
K. Strimmer
92
10
0
06 May 2010
Learning the Structure of Deep Sparse Graphical Models
Learning the Structure of Deep Sparse Graphical Models
Ryan P. Adams
Hanna M. Wallach
Zoubin Ghahramani
74
87
0
31 Dec 2009
Geometric Representations of Random Hypergraphs
Geometric Representations of Random Hypergraphs
Simón Lunagómez
S. Mukherjee
R. Wolpert
E. Airoldi
48
16
0
18 Dec 2009
Penalized Likelihood Methods for Estimation of Sparse High Dimensional
  Directed Acyclic Graphs
Penalized Likelihood Methods for Estimation of Sparse High Dimensional Directed Acyclic Graphs
Ali Shojaie
George Michailidis
CML
79
200
0
28 Nov 2009
Learning Bayesian Networks with the bnlearn R Package
Learning Bayesian Networks with the bnlearn R Package
M. Scutari
BDL
114
1,711
0
26 Aug 2009
Dependence Structure Estimation via Copula
Dependence Structure Estimation via Copula
Jian Ma
Zeng-qi Sun
43
9
0
28 Apr 2008
iBOA: The Incremental Bayesian Optimization Algorithm
iBOA: The Incremental Bayesian Optimization Algorithm
Martin Pelikan
K. Sastry
D. Goldberg
110
33
0
21 Jan 2008
Analysis of Estimation of Distribution Algorithms and Genetic Algorithms
  on NK Landscapes
Analysis of Estimation of Distribution Algorithms and Genetic Algorithms on NK Landscapes
Martin Pelikan
119
50
0
21 Jan 2008
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