scientific article; zbMATH DE number 7164719

zbMath1434.68459MaRDI QIDQ5214208

Kean Ming Tan, Tong Zhang, Han Liu, Junwei Lu

Publication date: 7 February 2020

Full work available at URL: http://jmlr.csail.mit.edu/papers/v20/17-525.html

Title: zbMATH Open Web Interface contents unavailable due to conflicting licenses.

zbMATH Keywords

model selectionsequential algorithmpersistencynonparametric regressionnonparametric graphical models

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Estimation in multivariate analysis (62H12) Learning and adaptive systems in artificial intelligence (68T05) Graphical methods in statistics (62A09)

Related Items

Regression in Tensor Product Spaces by the Method of Sieves

Uses Software

• hierNet

Cites Work

• Estimation of high-dimensional graphical models using regularized score matching
• Sparse inverse covariance estimation with the graphical lasso
• A lasso for hierarchical interactions
• Component selection and smoothing in multivariate nonparametric regression
• Functional additive regression
• Some extensions of score matching
• Additive regression and other nonparametric models
• Generalized additive models
• On the estimation of a probability density function by the maximum penalized likelihood method
• The cluster graphical Lasso for improved estimation of Gaussian graphical models
• Persistene in high-dimensional linear predictor-selection and the virtue of overparametrization
• Tensor product space ANOVA models.
• High-dimensional semiparametric Gaussian copula graphical models
• Sparse permutation invariant covariance estimation
• High-dimensional covariance estimation by minimizing \(\ell _{1}\)-penalized log-determinant divergence
• Fast and adaptive sparse precision matrix estimation in high dimensions
• Linear estimating equations for exponential families with application to Gaussian linear concentration models
• Adaptive piecewise polynomial estimation via trend filtering
• Introduction to empirical processes and semiparametric inference
• High-dimensional graphs and variable selection with the Lasso
• Bracketing metric entropy rates and empirical central limit theorems for function classes of Besov- and Sobolev-type
• On Graphical Models via Univariate Exponential Family Distributions
• Sparse Matrix Inversion with Scaled Lasso
• A Constrainedℓ₁Minimization Approach to Sparse Precision Matrix Estimation
• Model selection and estimation in the Gaussian graphical model
• Sparse Additive Models
• Model Selection for High-Dimensional Quadratic Regression via Regularization
• Interaction Screening for Ultrahigh-Dimensional Data
• Selection and estimation for mixed graphical models
• Partial Correlation Estimation by Joint Sparse Regression Models
• Variable Selection Using Adaptive Nonlinear Interaction Structures in High Dimensions
• Replicates in high dimensions, with applications to latent variable graphical models
• Convergence of a block coordinate descent method for nondifferentiable minimization
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item