Pages that link to "Item:Q2500458"
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The following pages link to High-dimensional graphs and variable selection with the Lasso (Q2500458):
Displaying 50 items.
- Estimation of high-dimensional low-rank matrices (Q548539) (← links)
- Estimation of (near) low-rank matrices with noise and high-dimensional scaling (Q548547) (← links)
- Sparse recovery under matrix uncertainty (Q605921) (← links)
- \(\ell_{1}\)-penalization for mixture regression models (Q619141) (← links)
- An inexact interior point method for \(L_{1}\)-regularized sparse covariance selection (Q621755) (← links)
- Consistent group selection in high-dimensional linear regression (Q627307) (← links)
- Adaptive Dantzig density estimation (Q629798) (← links)
- Inferring multiple graphical structures (Q637986) (← links)
- A majorization-minimization approach to variable selection using spike and slab priors (Q638812) (← links)
- Robust graphical modeling of gene networks using classical and alternative \(t\)-distributions (Q641155) (← links)
- Generalization of constraints for high dimensional regression problems (Q645414) (← links)
- The sparse Laplacian shrinkage estimator for high-dimensional regression (Q651021) (← links)
- Parametric or nonparametric? A parametricness index for model selection (Q651025) (← links)
- Modeling item-item similarities for personalized recommendations on Yahoo! front page (Q652346) (← links)
- Factor models and variable selection in high-dimensional regression analysis (Q661163) (← links)
- A greedy feature selection algorithm for big data of high dimensionality (Q669273) (← links)
- Interpreting latent variables in factor models via convex optimization (Q681494) (← links)
- High-dimensional structure estimation in Ising models: local separation criterion (Q693728) (← links)
- Nonconcave penalized composite conditional likelihood estimation of sparse Ising models (Q693730) (← links)
- High-dimensional regression with noisy and missing data: provable guarantees with nonconvexity (Q693741) (← links)
- Network inference and biological dynamics (Q714375) (← links)
- Some theoretical results on the grouped variables Lasso (Q734551) (← links)
- Fast global convergence of gradient methods for high-dimensional statistical recovery (Q741793) (← links)
- Regularized rank-based estimation of high-dimensional nonparanormal graphical models (Q741796) (← links)
- On confidence intervals for semiparametric expectile regression (Q746256) (← links)
- Estimating heterogeneous graphical models for discrete data with an application to roll call voting (Q746672) (← links)
- Learning relational dependency networks in hybrid domains (Q747248) (← links)
- Poisson dependency networks: gradient boosted models for multivariate count data (Q747270) (← links)
- A shrinkage principle for heavy-tailed data: high-dimensional robust low-rank matrix recovery (Q820791) (← links)
- Lasso-driven inference in time and space (Q820826) (← links)
- Fitting sparse linear models under the sufficient and necessary condition for model identification (Q826666) (← links)
- Bayesian hypothesis testing for Gaussian graphical models: conditional independence and order constraints (Q826923) (← links)
- Central limit theorem for linear spectral statistics of general separable sample covariance matrices with applications (Q826962) (← links)
- Maximum-type tests for high-dimensional regression coefficients using Wilcoxon scores (Q826977) (← links)
- Compound Poisson models for weighted networks with applications in finance (Q829212) (← links)
- Learning high-dimensional Gaussian linear structural equation models with heterogeneous error variances (Q829714) (← links)
- Promote sign consistency in the joint estimation of precision matrices (Q830115) (← links)
- Conditional score matching for high-dimensional partial graphical models (Q830589) (← links)
- Some sharp performance bounds for least squares regression with \(L_1\) regularization (Q834334) (← links)
- Near-ideal model selection by \(\ell _{1}\) minimization (Q834335) (← links)
- High-dimensional variable selection (Q834336) (← links)
- High-dimensional analysis of semidefinite relaxations for sparse principal components (Q834367) (← links)
- Sparsity in penalized empirical risk minimization (Q838303) (← links)
- Best subset selection, persistence in high-dimensional statistical learning and optimization under \(l_1\) constraint (Q869974) (← links)
- Computational implications of reducing data to sufficient statistics (Q887274) (← links)
- Globally adaptive quantile regression with ultra-high dimensional data (Q888510) (← links)
- The performance of covariance selection methods that consider decomposable models only (Q899046) (← links)
- Estimation of the inverse scatter matrix of an elliptically symmetric distribution (Q900790) (← links)
- High dimensional posterior convergence rates for decomposable graphical models (Q902216) (← links)
- Network assisted analysis to reveal the genetic basis of autism (Q902933) (← links)
