$High-Dimensional Poisson DAG Model Learning Using $\ell_1$-Regularized Regression$

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High-Dimensional Poisson DAG Model Learning Using $\ell_1$ -Regularized Regression

5 October 2018

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Papers citing "High-Dimensional Poisson DAG Model Learning Using $\ell_1$-Regularized Regression"

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Title
On Causal Discovery with Equal Variance Assumption Wenyu Chen Mathias Drton Y Samuel Wang CML 73 85 0 09 Jul 2018
Learning linear structural equation models in polynomial time and sample complexity Asish Ghoshal Jean Honorio CML 83 84 0 15 Jul 2017
Learning Quadratic Variance Function (QVF) DAG models via OverDispersion Scoring (ODS) G. Park Garvesh Raskutti CML 94 45 0 28 Apr 2017
Sparse Poisson Regression with Penalized Weighted Score Function Jinzhu Jia Fang Xie Lihu Xu 83 16 0 11 Mar 2017
Learning Identifiable Gaussian Bayesian Networks in Polynomial Time and Sample Complexity Asish Ghoshal Jean Honorio CML TPM 75 55 0 03 Mar 2017
A Review of Multivariate Distributions for Count Data Derived from the Poisson Distribution David I. Inouye Eunho Yang Genevera I. Allen Pradeep Ravikumar 65 115 0 31 Aug 2016
Information-theoretic limits of Bayesian network structure learning Asish Ghoshal Jean Honorio 130 25 0 27 Jan 2016
High-dimensional learning of linear causal networks via inverse covariance estimation Po-Ling Loh Peter Buhlmann CML 115 189 0 14 Nov 2013
CAM: Causal additive models, high-dimensional order search and penalized regression Peter Buhlmann J. Peters J. Ernest CML 119 325 0 06 Oct 2013
Learning Bayesian Networks: The Combination of Knowledge and Statistical Data David Heckerman D. Geiger D. M. Chickering TPM 117 3,982 0 27 Feb 2013
Directed Cyclic Graphical Representations of Feedback Models Peter Spirtes CML 112 239 0 20 Feb 2013
On Graphical Models via Univariate Exponential Family Distributions Eunho Yang Pradeep Ravikumar Genevera I. Allen Zhandong Liu 68 173 0 17 Jan 2013
Geometry of the faithfulness assumption in causal inference Caroline Uhler Garvesh Raskutti Peter Buhlmann B. Yu 114 222 0 02 Jul 2012
Identifiability of Gaussian structural equation models with equal error variances J. Peters Peter Buhlmann CML 175 338 0 11 May 2012
Identifiability of Causal Graphs using Functional Models J. Peters Joris Mooij Dominik Janzing Bernhard Schölkopf 94 155 0 14 Feb 2012
DirectLiNGAM: A direct method for learning a linear non-Gaussian structural equation model Shohei Shimizu Takanori Inazumi Yasuhiro Sogawa Aapo Hyvarinen Yoshinobu Kawahara Takashi Washio P. Hoyer K. Bollen CML 102 512 0 13 Jan 2011
$High-dimensional covariance estimation by minimizing $\ell_1$-penalized log-determinant divergence$ High-dimensional covariance estimation by minimizing $\ell_1$ -penalized log-determinant divergence Pradeep Ravikumar Martin J. Wainwright Garvesh Raskutti Bin Yu 247 872 0 21 Nov 2008
$High-Dimensional Graphical Model Selection Using $\ell_1$-Regularized Logistic Regression$ High-Dimensional Graphical Model Selection Using $\ell_1$ -Regularized Logistic Regression Pradeep Ravikumar Martin J. Wainwright John D. Lafferty 305 177 0 26 Apr 2008