$High-dimensional covariance estimation by minimizing $\ell_1$-penalized log-determinant divergence$

High-dimensional covariance estimation by minimizing $\ell_1$ -penalized log-determinant divergence

21 November 2008

Papers citing "High-dimensional covariance estimation by minimizing $\ell_1$-penalized log-determinant divergence"

50 / 335 papers shown

Title
Efficient Statistics for Sparse Graphical Models from Truncated Samples Arnab Bhattacharyya Rathin Desai Sai Ganesh Nagarajan Ioannis Panageas 9 4 0 17 Jun 2020
Estimating High-dimensional Covariance and Precision Matrices under General Missing Dependence Seongoh Park Xinlei Wang Johan Lim 6 13 0 08 Jun 2020
Thresholded Adaptive Validation: Tuning the Graphical Lasso for Graph Recovery M. Laszkiewicz Asja Fischer Johannes Lederer 14 5 0 01 May 2020
Dependence in elliptical partial correlation graphs D. Rossell Piotr Zwiernik 6 17 0 28 Apr 2020
Beyond Data Samples: Aligning Differential Networks Estimation with Scientific Knowledge Arshdeep Sekhon Zhe Wang Yanjun Qi 12 0 0 24 Apr 2020
Estimation of sparse Gaussian graphical models with hidden clustering structure Meixia Lin Defeng Sun Kim-Chuan Toh Chengjing Wang 9 3 0 17 Apr 2020
Bayesian inference for high-dimensional decomposable graphs Kyoungjae Lee Xuan Cao 13 6 0 17 Apr 2020
A partial graphical model with a structural prior on the direct links between predictors and responses Eunice Okome Obiang Pascal Jézéquel Frédéric Proia 11 2 0 26 Mar 2020
FuDGE: A Method to Estimate a Functional Differential Graph in a High-Dimensional Setting Boxin Zhao Y Samuel Wang Mladen Kolar 11 10 0 11 Mar 2020
Gaussian Graphical Model exploration and selection in high dimension low sample size setting Thomas Lartigue Simona Bottani Stéphanie Baron O. Colliot S. Durrleman S. Allassonnière 24 6 0 11 Mar 2020
Learning Gaussian Graphical Models via Multiplicative Weights Anamay Chaturvedi Jonathan Scarlett 26 3 0 20 Feb 2020
Imputation for High-Dimensional Linear Regression Kabir Chandrasekher A. Alaoui Andrea Montanari 27 5 0 24 Jan 2020
Graph quilting: graphical model selection from partially observed covariances Giuseppe Vinci Gautam Dasarathy Genevera I. Allen CML 10 20 0 11 Dec 2019
Graph estimation for Gaussian data zero-inflated by double truncation Gégout-Petit Anne Gueudin-Muller Aurélie Karmann Clémence 9 3 0 18 Nov 2019
Estimation of dynamic networks for high-dimensional nonstationary time series Mengyu Xu Xiaohui Chen Weichi Wu AI4TS 26 7 0 14 Nov 2019
Partial Separability and Functional Graphical Models for Multivariate Gaussian Processes Javier Zapata Sang-Yun Oh Alexander Petersen 11 38 0 07 Oct 2019
Distance-learning For Approximate Bayesian Computation To Model a Volcanic Eruption Lorenzo Pacchiardi Pierre Künzli Marcel Schoengens B. Chopard Ritabrata Dutta 20 13 0 28 Sep 2019
Forecaster: A Graph Transformer for Forecasting Spatial and Time-Dependent Data Yongqian Li J. M. F. Moura AI4TS 27 28 0 09 Sep 2019
Graph-based Transforms for Video Coding Hilmi E. Egilmez Y. Chao Antonio Ortega 9 25 0 03 Sep 2019
Graph inference with clustering and false discovery rate control Tabea Rebafka Étienne Roquain Fanny Villers 31 6 0 23 Jul 2019
Feature Graph Learning for 3D Point Cloud Denoising Wei Hu Xiang Gao Gene Cheung Zongming Guo 23 87 0 22 Jul 2019
Change point detection for graphical models in the presence of missing values Malte Londschien Solt Kovács Peter Buhlmann 22 28 0 11 Jul 2019
High-dimensional Gaussian graphical model for network-linked data Tianxi Li Cheng Qian Elizaveta Levina Ji Zhu 14 15 0 04 Jul 2019
A greedy algorithm for sparse precision matrix approximation Didi Lv Xiaoqun Zhang 16 1 0 01 Jul 2019
Direct Learning with Guarantees of the Difference DAG Between Structural Equation Models Asish Ghoshal Kevin Bello Jean Honorio CML 14 8 0 28 Jun 2019
Efficient Covariance Estimation from Temporal Data Hrayr Harutyunyan Daniel Moyer Hrant Khachatrian Greg Ver Steeg Aram Galstyan 16 2 0 30 May 2019
Learning Gaussian DAGs from Network Data Hangjian Li Oscar Hernan Madrid Padilla Qing Zhou CML 22 2 0 26 May 2019
Learning Clique Forests Guido Previde Massara T. Aste 26 16 0 06 May 2019
Learning Some Popular Gaussian Graphical Models without Condition Number Bounds Jonathan A. Kelner Frederic Koehler Raghu Meka Ankur Moitra 25 32 0 03 May 2019
Learning Dependency Structures for Weak Supervision Models P. Varma Frederic Sala A. He Alexander Ratner Christopher Ré NoLa 19 67 0 14 Mar 2019
Ising Models with Latent Conditional Gaussian Variables Frank Nussbaum Joachim Giesen CML 17 6 0 28 Jan 2019
High Dimensional Robust $M$ -Estimation: Arbitrary Corruption and Heavy Tails L. Liu Tianyang Li C. Caramanis 18 14 0 24 Jan 2019
Generalized Score Matching for Non-Negative Data Shiqing Yu Mathias Drton Ali Shojaie 19 2 0 26 Dec 2018
Structure Learning of Sparse GGMs over Multiple Access Networks Mostafa Tavassolipour Armin Karamzade Reza Mirzaeifard S. Motahari M. M. Manzuri Shalmani 19 2 0 26 Dec 2018
An efficient ADMM algorithm for high dimensional precision matrix estimation via penalized quadratic loss Cheng-Long Wang Binyan Jiang 4 25 0 12 Nov 2018
Scale calibration for high-dimensional robust regression Yu Li 19 25 0 06 Nov 2018
RSVP-graphs: Fast High-dimensional Covariance Matrix Estimation under Latent Confounding Rajen Dinesh Shah Benjamin Frot Gian-Andrea Thanei N. Meinshausen 19 6 0 02 Nov 2018
$High-Dimensional Poisson DAG Model Learning Using $\ell_1$-Regularized Regression$ High-Dimensional Poisson DAG Model Learning Using $\ell_1$ -Regularized Regression G. Park Sion Park 15 18 0 05 Oct 2018
High-Temperature Structure Detection in Ferromagnets Yuan Cao Matey Neykov Han Liu 24 10 0 21 Sep 2018
Learning of Tree-Structured Gaussian Graphical Models on Distributed Data under Communication Constraints Mostafa Tavassolipour S. Motahari M. Manzuri-Shalmani 11 8 0 21 Sep 2018
A convex formulation for high-dimensional sparse sliced inverse regression Kean Ming Tan Zhaoran Wang Tong Zhang Han Liu R. Cook 9 36 0 17 Sep 2018
Learning high-dimensional graphical models with regularized quadratic scoring Eric Janofsky 14 1 0 15 Sep 2018
Uniform Inference in High-Dimensional Gaussian Graphical Models Jan Rabenseifner Jannis Kuck Martin Spindler Victor Chernozhukov 14 6 0 30 Aug 2018
On Causal Discovery with Equal Variance Assumption Wenyu Chen Mathias Drton Y Samuel Wang CML 19 84 0 09 Jul 2018
High-Dimensional Inference for Cluster-Based Graphical Models Carson Eisenach F. Bunea Y. Ning Claudiu Dinicu 12 8 0 13 Jun 2018
Valid Post-selection Inference in Assumption-lean Linear Regression Arun K. Kuchibhotla L. Brown A. Buja E. George Linda H. Zhao 11 13 0 11 Jun 2018
Identifiability in Gaussian Graphical Models D. Soh S. Tatikonda 34 3 0 10 Jun 2018
Stationary Geometric Graphical Model Selection I. Soloveychik Vahid Tarokh 13 0 0 10 Jun 2018
A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models Beilun Wang Arshdeep Sekhon Yanjun Qi 13 6 0 01 Jun 2018
M-estimation with the Trimmed l1 Penalty Jihun Yun P. Zheng Eunho Yang A. Lozano Aleksandr Aravkin 19 0 0 19 May 2018