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Extended Bayesian Information Criteria for Gaussian Graphical Models

Extended Bayesian Information Criteria for Gaussian Graphical Models

30 November 2010
Rina Foygel
Mathias Drton
ArXivPDFHTML

Papers citing "Extended Bayesian Information Criteria for Gaussian Graphical Models"

31 / 31 papers shown
Title
Adaptive Bayesian Multivariate Spline Knot Inference with Prior
  Specifications on Model Complexity
Adaptive Bayesian Multivariate Spline Knot Inference with Prior Specifications on Model Complexity
Junhui He
Ying Yang
Jian Kang
27
0
0
22 May 2024
Network reconstruction via the minimum description length principle
Network reconstruction via the minimum description length principle
Tiago P. Peixoto
23
5
0
02 May 2024
Human-in-the-Loop Causal Discovery under Latent Confounding using
  Ancestral GFlowNets
Human-in-the-Loop Causal Discovery under Latent Confounding using Ancestral GFlowNets
Tiago da Silva
Eliezer de Souza da Silva
Adèle H. Ribeiro
António Góis
Dominik Heider
Samuel Kaski
Diego Mesquita
CML
54
6
0
21 Sep 2023
On the application of Gaussian graphical models to paired data problems
On the application of Gaussian graphical models to paired data problems
Saverio Ranciati
A. Roverato
34
1
0
26 Jul 2023
Testing Sparsity Assumptions in Bayesian Networks
Testing Sparsity Assumptions in Bayesian Networks
Luke Duttweiler
Sally W. Thurston
A. Almudevar
26
0
0
12 Jul 2023
On Learning Time Series Summary DAGs: A Frequency Domain Approach
On Learning Time Series Summary DAGs: A Frequency Domain Approach
Aramayis Dallakyan
CML
AI4TS
30
3
0
17 Apr 2023
High-Dimensional Undirected Graphical Models for Arbitrary Mixed Data
High-Dimensional Undirected Graphical Models for Arbitrary Mixed Data
Konstantin Göbler
Anne Miloschewski
Mathias Drton
S. Mukherjee
19
2
0
21 Nov 2022
An Experimental Study of Dimension Reduction Methods on Machine Learning
  Algorithms with Applications to Psychometrics
An Experimental Study of Dimension Reduction Methods on Machine Learning Algorithms with Applications to Psychometrics
Sean H. Merritt
A. Christensen
11
3
0
19 Oct 2022
Multi-View Independent Component Analysis with Shared and Individual
  Sources
Multi-View Independent Component Analysis with Shared and Individual Sources
T. Pandeva
Patrick Forré
CML
15
5
0
05 Oct 2022
Fast and Accurate Graph Learning for Huge Data via Minipatch Ensembles
Fast and Accurate Graph Learning for Huge Data via Minipatch Ensembles
Tianyi Yao
Minjie Wang
Genevera I. Allen
16
1
0
22 Oct 2021
GLIME: A new graphical methodology for interpretable model-agnostic
  explanations
GLIME: A new graphical methodology for interpretable model-agnostic explanations
Zoumpolia Dikopoulou
S. Moustakidis
Patrik Karlsson
15
6
0
21 Jul 2021
DAGs with No Curl: An Efficient DAG Structure Learning Approach
DAGs with No Curl: An Efficient DAG Structure Learning Approach
Yue Yu
Tian Gao
Naiyu Yin
Q. Ji
CML
30
59
0
14 Jun 2021
Online Structural Change-point Detection of High-dimensional Streaming
  Data via Dynamic Sparse Subspace Learning
Online Structural Change-point Detection of High-dimensional Streaming Data via Dynamic Sparse Subspace Learning
Ruiyu Xu
Jianguo Wu
Xiaowei Yue
Yongxiang Li
30
8
0
24 Sep 2020
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
13
479
0
26 Jun 2020
Structure Learning for Cyclic Linear Causal Models
Structure Learning for Cyclic Linear Causal Models
Carlos Améndola
Philipp Dettling
Mathias Drton
Federica Onori
Jun Wu
CML
15
15
0
10 Jun 2020
Certifiably Optimal Sparse Inverse Covariance Estimation
Certifiably Optimal Sparse Inverse Covariance Estimation
Dimitris Bertsimas
Jourdain Lamperski
J. Pauphilet
22
13
0
25 Jun 2019
Predictive Learning on Hidden Tree-Structured Ising Models
Predictive Learning on Hidden Tree-Structured Ising Models
Konstantinos E. Nikolakakis
Dionysios S. Kalogerias
Anand D. Sarwate
23
12
0
11 Dec 2018
PANDA: AdaPtive Noisy Data Augmentation for Regularization of Undirected
  Graphical Models
PANDA: AdaPtive Noisy Data Augmentation for Regularization of Undirected Graphical Models
Yinan Li
Xiao Liu
Fang Liu
29
7
0
11 Oct 2018
Robust Bayesian Model Selection for Variable Clustering with the
  Gaussian Graphical Model
Robust Bayesian Model Selection for Variable Clustering with the Gaussian Graphical Model
Daniel Andrade
Akiko Takeda
Kenji Fukumizu
29
4
0
15 Jun 2018
Model-based Clustering with Sparse Covariance Matrices
Model-based Clustering with Sparse Covariance Matrices
Michael Fop
T. B. Murphy
Luca Scrucca
34
39
0
21 Nov 2017
Quantile Graphical Models: Prediction and Conditional Independence with
  Applications to Systemic Risk
Quantile Graphical Models: Prediction and Conditional Independence with Applications to Systemic Risk
A. Belloni
Mingli Chen
Victor Chernozhukov
19
7
0
01 Jul 2016
Generalized Network Psychometrics: Combining Network and Latent Variable
  Models
Generalized Network Psychometrics: Combining Network and Latent Variable Models
S. Epskamp
M. Rhemtulla
D. Borsboom
17
424
0
30 May 2016
Generalized Stability Approach for Regularized Graphical Models
Generalized Stability Approach for Regularized Graphical Models
Christian L. Müller
Richard Bonneau
Zachary D. Kurtz
30
21
0
23 May 2016
Sparse Estimation of Multivariate Poisson Log-Normal Models from Count
  Data
Sparse Estimation of Multivariate Poisson Log-Normal Models from Count Data
Hao Wu
Xinwei Deng
Naren Ramakrishnan
8
16
0
22 Feb 2016
High-dimensional consistency in score-based and hybrid structure
  learning
High-dimensional consistency in score-based and hybrid structure learning
Preetam Nandy
Alain Hauser
Marloes H. Maathuis
39
129
0
09 Jul 2015
Stratified Gaussian Graphical Models
Stratified Gaussian Graphical Models
Henrik J. Nyman
J. Pensar
J. Corander
25
7
0
08 Sep 2014
L0 Sparse Inverse Covariance Estimation
L0 Sparse Inverse Covariance Estimation
G. Marjanovic
Alfred Hero
27
38
0
05 Aug 2014
Estimation of positive definite M-matrices and structure learning for
  attractive Gaussian Markov Random fields
Estimation of positive definite M-matrices and structure learning for attractive Gaussian Markov Random fields
M. Slawski
Matthias Hein
43
104
0
26 Apr 2014
Bayesian model choice and information criteria in sparse generalized
  linear models
Bayesian model choice and information criteria in sparse generalized linear models
Rina Foygel
Mathias Drton
45
62
0
23 Dec 2011
Fast-rate and optimistic-rate error bounds for L1-regularized regression
Fast-rate and optimistic-rate error bounds for L1-regularized regression
Rina Foygel
Nathan Srebro
66
7
0
01 Aug 2011
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
56
90
0
06 Jul 2011
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