Graphical methods for efficient likelihood inference in Gaussian
covariance models

v1v2 (latest)

Graphical methods for efficient likelihood inference in Gaussian covariance models

Journal of machine learning research (JMLR), 2007

9 August 2007

Thomas S. Richardson

ArXiv (abs)PDF HTML

Papers citing "Graphical methods for efficient likelihood inference in Gaussian covariance models"

15 / 15 papers shown

Title
Stochastic Causal Programming for Bounding Treatment EffectsCLEaR (CLEaR), 2022 Kirtan Padh Jakob Zeitler David S. Watson Matt J. Kusner Ricardo M. A. Silva Niki Kilbertus CML 207 26 0 22 Feb 2022
Structured Graph Learning Via Laplacian Spectral ConstraintsNeural Information Processing Systems (NeurIPS), 2019 Sandeep Kumar Jiaxi Ying J. Cardoso Daniel P. Palomar 184 59 0 24 Sep 2019
A Unified Framework for Structured Graph Learning via Spectral Constraints Sandeep Kumar Jiaxi Ying José Vinícius de Miranda Cardoso Daniel P. Palomar 194 123 0 22 Apr 2019
The Maximum Likelihood Threshold of a Path Diagram Mathias Drton C. Fox Andreas Kaufl G. Pouliot 98 9 0 14 May 2018
Learning from Pairwise Marginal IndependenciesConference on Uncertainty in Artificial Intelligence (UAI), 2015 J. Textor Alexander Idelberger Maciej Liskiewicz CML 173 10 0 02 Aug 2015
Robust Graphical Modeling with t-DistributionsConference on Uncertainty in Artificial Intelligence (UAI), 2009 Michael Finegold Mathias Drton 61 20 0 09 Aug 2014
Learning Graphical Models With HubsJournal of machine learning research (JMLR), 2014 Kean Ming Tan Palma London Karthika Mohan Su-In Lee Maryam Fazel Daniela Witten 207 101 0 28 Feb 2014
Concave Penalized Estimation of Sparse Gaussian Bayesian NetworksJournal of machine learning research (JMLR), 2014 Bryon Aragam Qing Zhou CML 341 116 0 04 Jan 2014
On the causal interpretation of acyclic mixed graphs under multivariate normality C. Fox Andreas Kaufl Mathias Drton CML 227 10 0 16 Aug 2013
Groups acting on Gaussian graphical models J. Draisma S. Kuhnt Piotr Zwiernik 173 7 0 25 Jul 2012
Maximum likelihood fitting of acyclic directed mixed graphs to binary dataConference on Uncertainty in Artificial Intelligence (UAI), 2010 R. Evans Thomas S. Richardson 151 25 0 15 Mar 2012
Wishart distributions for decomposable covariance graph models Kshitij Khare B. Rajaratnam 194 71 0 09 Mar 2011
Robust graphical modeling of gene networks using classical and alternative T-distributions Michael Finegold Mathias Drton 238 116 0 19 Sep 2010
Discrete chain graph models Mathias Drton 319 129 0 04 Sep 2009
A Localization Approach to Improve Iterative Proportional Scaling in Gaussian Graphical Models Hisayuki Hara Akimichi Takemura 247 15 0 19 Feb 2008

We use cookies and other tracking technologies to improve your browsing experience on our website, to show you personalized content and targeted ads, to analyze our website traffic, and to understand where our visitors are coming from. See our policy.