Differential network inference via the fused D-trace loss with cross variables
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Publication:2180062
DOI10.1214/20-EJS1691zbMath1439.62232MaRDI QIDQ2180062
Yichong Wu, Xiao-Ping Liu, Luo-Nan Chen, Tie-Jun Li
Publication date: 13 May 2020
Published in: Electronic Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://projecteuclid.org/euclid.ejs/1585101683
Computational methods for problems pertaining to statistics (62-08) Applications of statistics to biology and medical sciences; meta analysis (62P10) General biostatistics (92B15) Nonparametric estimation (62G05) Numerical optimization and variational techniques (65K10)
Uses Software
Cites Work
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- A coordinate gradient descent method for \(\ell_{1}\)-regularized convex minimization
- A shrinkage principle for heavy-tailed data: high-dimensional robust low-rank matrix recovery
- High-dimensional covariance estimation by minimizing \(\ell _{1}\)-penalized log-determinant divergence
- Sub-Gaussian estimators of the mean of a random matrix with heavy-tailed entries
- Detecting direct associations in a network by information theoretic approaches
- Coordinate descent algorithms for lasso penalized regression
- High-dimensional graphs and variable selection with the Lasso
- Direct estimation of differential networks
- A Constrainedℓ1Minimization Approach to Sparse Precision Matrix Estimation
- Model selection and estimation in the Gaussian graphical model
- The Joint Graphical Lasso for Inverse Covariance Estimation Across Multiple Classes
- Regularization and Variable Selection Via the Elastic Net
- Differential network analysis via lasso penalized D-trace loss
- Sparse precision matrix estimation via lasso penalized D-trace loss
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