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precision matrix

58 papers

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Co-occurring keywords

graphical model (864) gaussian graphical model (106) sparse estimation (88) precision matrix estimation (27) sparse optimization (246) graphical lasso (31) bayesian inference (1907) inverse covariance (20) covariance estimation (98) sparse regression (175)

Papers

Extremal graphical modeling with latent variables via convex optimization JMLR 2025
DNNLasso: Scalable Graph Learning for Matrix-Variate Data AISTATS 2024
Fair GLASSO: Estimating Fair Graphical Models with Unbiased Statistical Behavior NIPS 2024
FasMe: Fast and Sample-efficient Meta Estimator for Precision Matrix Learning in Small Sample Settings NIPS 2024
Evidence Estimation in Gaussian Graphical Models Using a Telescoping Block Decomposition of the Precision Matrix JMLR 2024
Efficient Graph Laplacian Estimation by Proximal Newton AISTATS 2024
Adaptive Estimation of Graphical Models under Total Positivity ICML 2023
Conditional Matrix Flows for Gaussian Graphical Models NIPS 2023
MARS: A Second-Order Reduction Algorithm for High-Dimensional Sparse Precision Matrices Estimation JMLR 2023
Intervention target estimation in the presence of latent variables UAI 2022
Estimating graphical models for count data with applications to single-cell gene network NIPS 2022
The Dual PC Algorithm for Structure Learning PGM 2022
Variational nearest neighbor Gaussian process ICML 2022
Bayesian Covariate-Dependent Gaussian Graphical Models with Varying Structure JMLR 2022
Scalable Intervention Target Estimation in Linear Models NIPS 2021
Meta Learning for Support Recovery in High-dimensional Precision Matrix Estimation ICML 2021
Simultaneous Change Point Inference and Structure Recovery for High Dimensional Gaussian Graphical Models JMLR 2021
On the Theoretical Guarantees for Parameter Estimation of Gaussian Random Field Models: A Sparse Precision Matrix Approach JMLR 2020
Fast Bayesian Inference of Sparse Networks with Automatic Sparsity Determination JMLR 2020
Sequential change-point detection in high-dimensional Gaussian graphical models JMLR 2020
Quantile Graphical Models: a Bayesian Approach JMLR 2020
Nonconvex Sparse Graph Learning under Laplacian Constrained Graphical Model NIPS 2020
Learning Some Popular Gaussian Graphical Models without Condition Number Bounds NIPS 2020
High-dimensional Gaussian graphical models on network-linked data JMLR 2020
EiGLasso: Scalable Estimation of Cartesian Product of Sparse Inverse Covariance Matrices UAI 2020