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High-dimensional consistency in score-based and hybrid structure
  learning

High-dimensional consistency in score-based and hybrid structure learning

9 July 2015
Preetam Nandy
Alain Hauser
Marloes H. Maathuis
ArXivPDFHTML

Papers citing "High-dimensional consistency in score-based and hybrid structure learning"

20 / 20 papers shown
Title
Characterization and Greedy Learning of Gaussian Structural Causal Models under Unknown Interventions
Characterization and Greedy Learning of Gaussian Structural Causal Models under Unknown Interventions
Juan L. Gamella
Armeen Taeb
C. Heinze-Deml
Peter Buhlmann
CML
106
8
0
13 Mar 2025
The huge Package for High-dimensional Undirected Graph Estimation in R
The huge Package for High-dimensional Undirected Graph Estimation in R
T. Zhao
Han Liu
Kathryn Roeder
John D. Lafferty
Larry A. Wasserman
34
480
0
26 Jun 2020
Complete Graphical Characterization and Construction of Adjustment Sets
  in Markov Equivalence Classes of Ancestral Graphs
Complete Graphical Characterization and Construction of Adjustment Sets in Markov Equivalence Classes of Ancestral Graphs
Emilija Perković
J. Textor
M. Kalisch
Marloes H. Maathuis
OffRL
39
144
0
22 Jun 2016
Scaling up Greedy Causal Search for Continuous Variables
Scaling up Greedy Causal Search for Continuous Variables
Joseph Ramsey
LRM
29
41
0
28 Jul 2015
Selective Greedy Equivalence Search: Finding Optimal Bayesian Networks
  Using a Polynomial Number of Score Evaluations
Selective Greedy Equivalence Search: Finding Optimal Bayesian Networks Using a Polynomial Number of Score Evaluations
D. M. Chickering
Christopher Meek
59
28
0
06 Jun 2015
The Recovery of Causal Poly-Trees from Statistical Data
The Recovery of Causal Poly-Trees from Statistical Data
George Rebane
Judea Pearl
CML
43
212
0
27 Mar 2013
Causal Inference and Causal Explanation with Background Knowledge
Causal Inference and Causal Explanation with Background Knowledge
Christopher Meek
CML
233
630
0
20 Feb 2013
Learning Equivalence Classes of Bayesian Networks Structures
Learning Equivalence Classes of Bayesian Networks Structures
D. M. Chickering
56
831
0
13 Feb 2013
Learning Bayesian Network Structure from Massive Datasets: The "Sparse
  Candidate" Algorithm
Learning Bayesian Network Structure from Massive Datasets: The "Sparse Candidate" Algorithm
N. Friedman
I. Nachman
Dana Peér
118
654
0
23 Jan 2013
Finding Optimal Bayesian Networks
Finding Optimal Bayesian Networks
D. M. Chickering
Christopher Meek
TPM
58
152
0
12 Dec 2012
Order-independent constraint-based causal structure learning
Order-independent constraint-based causal structure learning
Diego Colombo
Marloes H. Maathuis
CML
82
597
0
14 Nov 2012
Geometry of the faithfulness assumption in causal inference
Geometry of the faithfulness assumption in causal inference
Caroline Uhler
Garvesh Raskutti
Peter Buhlmann
B. Yu
80
220
0
02 Jul 2012
$\ell_0$-penalized maximum likelihood for sparse directed acyclic graphs
ℓ0\ell_0ℓ0​-penalized maximum likelihood for sparse directed acyclic graphs
Sara van de Geer
Peter Buhlmann
CML
102
83
0
24 May 2012
Kernel-based Conditional Independence Test and Application in Causal
  Discovery
Kernel-based Conditional Independence Test and Application in Causal Discovery
Kun Zhang
J. Peters
Dominik Janzing
Bernhard Schölkopf
BDL
CML
64
618
0
14 Feb 2012
High Dimensional Semiparametric Gaussian Copula Graphical Models
High Dimensional Semiparametric Gaussian Copula Graphical Models
Han Liu
Fang Han
M. Yuan
John D. Lafferty
Larry A. Wasserman
75
407
0
10 Feb 2012
High-Dimensional Gaussian Graphical Model Selection: Walk Summability
  and Local Separation Criterion
High-Dimensional Gaussian Graphical Model Selection: Walk Summability and Local Separation Criterion
Anima Anandkumar
Vincent Y. F. Tan
A. Willsky
72
90
0
06 Jul 2011
Characterization and Greedy Learning of Interventional Markov
  Equivalence Classes of Directed Acyclic Graphs
Characterization and Greedy Learning of Interventional Markov Equivalence Classes of Directed Acyclic Graphs
Alain Hauser
Peter Buhlmann
CML
54
425
0
14 Apr 2011
Extended Bayesian Information Criteria for Gaussian Graphical Models
Extended Bayesian Information Criteria for Gaussian Graphical Models
Rina Foygel
Mathias Drton
80
866
0
30 Nov 2010
Learning Bayesian Networks with the bnlearn R Package
Learning Bayesian Networks with the bnlearn R Package
M. Scutari
BDL
120
1,723
0
26 Aug 2009
High-dimensional covariance estimation by minimizing $\ell_1$-penalized
  log-determinant divergence
High-dimensional covariance estimation by minimizing ℓ1\ell_1ℓ1​-penalized log-determinant divergence
Pradeep Ravikumar
Martin J. Wainwright
Garvesh Raskutti
Bin Yu
159
874
0
21 Nov 2008
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