Graph informed sliced inverse regression
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Publication:2242175
DOI10.1016/j.csda.2021.107302OpenAlexW3174500029MaRDI QIDQ2242175
Eugen Pircalabelu, Andreas Artemiou
Publication date: 9 November 2021
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.csda.2021.107302
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Cites Work
- Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
- Sparse inverse covariance estimation with the graphical lasso
- Sparse Sliced Inverse Regression Via Lasso
- Principal support vector machines for linear and nonlinear sufficient dimension reduction
- Dimension estimation in sufficient dimension reduction: a unifying approach
- Covariance regularization by thresholding
- Nonconcave penalized inverse regression in single-index models with high dimensional predic\-tors
- On hybrid methods of inverse regression-based algorithms
- A nonlinear multi-dimensional variable selection method for high dimensional data: sparse MAVE
- Sparsistency and rates of convergence in large covariance matrix estimation
- Penalized principal logistic regression for sparse sufficient dimension reduction
- On consistency and sparsity for sliced inverse regression in high dimensions
- The graphical lasso: new insights and alternatives
- High dimensional single index models
- Regularized estimation of large covariance matrices
- High-dimensional graphs and variable selection with the Lasso
- Contour regression: a general approach to dimension reduction
- Joint estimation of multiple graphical models
- On Directional Regression for Dimension Reduction
- Sliced Inverse Regression for Dimension Reduction
- On Principal Hessian Directions for Data Visualization and Dimension Reduction: Another Application of Stein's Lemma
- Shrinking characteristics of precision matrix estimators
- An Adaptive Estimation of Dimension Reduction Space
- A Review on Dimension Reduction
- The Joint Graphical Lasso for Inverse Covariance Estimation Across Multiple Classes
- Combining eigenvalues and variation of eigenvectors for order determination
- Principal weighted support vector machines for sufficient dimension reduction in binary classification
- Sparse precision matrix estimation via lasso penalized D-trace loss
- Sparse sufficient dimension reduction
- Differential Geometric Least Angle Regression: A Differential Geometric Approach to Sparse Generalized Linear Models
- On Sliced Inverse Regression With High-Dimensional Covariates
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