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.
- Gemini: graph estimation with matrix variate normal instances (Q2249840) (← links)
- Robust subspace clustering (Q2249846) (← links)
- Lasso with long memory regression errors (Q2250693) (← links)
- Fast and adaptive sparse precision matrix estimation in high dimensions (Q2256755) (← links)
- Sparse semiparametric discriminant analysis (Q2256757) (← links)
- High-dimensional variable screening and bias in subsequent inference, with an empirical comparison (Q2259726) (← links)
- A global homogeneity test for high-dimensional linear regression (Q2263711) (← links)
- Network exploration via the adaptive LASSO and SCAD penalties (Q2270657) (← links)
- Treelets -- an adaptive multi-scale basis for sparse unordered data (Q2271330) (← links)
- Data science, big data and statistics (Q2273155) (← links)
- NOVELIST estimator of large correlation and covariance matrices and their inverses (Q2273174) (← links)
- Quasi-Bayesian estimation of large Gaussian graphical models (Q2274970) (← links)
- Consistency of Bayesian linear model selection with a growing number of parameters (Q2276179) (← links)
- Network classification with applications to brain connectomics (Q2281212) (← links)
- Variable selection via adaptive false negative control in linear regression (Q2283578) (← links)
- Sorted concave penalized regression (Q2284364) (← links)
- Physics informed topology learning in networks of linear dynamical systems (Q2288709) (← links)
- Spatial disease mapping using directed acyclic graph auto-regressive (DAGAR) models (Q2290712) (← links)
- Hierarchical normalized completely random measures for robust graphical modeling (Q2290716) (← links)
- Efficient computation for differential network analysis with applications to quadratic discriminant analysis (Q2291319) (← links)
- Robust regression via mutivariate regression depth (Q2295029) (← links)
- Variable selection with spatially autoregressive errors: a generalized moments Lasso estimator (Q2297950) (← links)
- Compressed covariance estimation with automated dimension learning (Q2300095) (← links)
- A review of Gaussian Markov models for conditional independence (Q2301082) (← links)
- Changepoint detection by the quantile Lasso method (Q2301226) (← links)
- High-dimensional regression in practice: an empirical study of finite-sample prediction, variable selection and ranking (Q2302521) (← links)
- Large-scale local causal inference of gene regulatory relationships (Q2302806) (← links)
- A two-stage sequential conditional selection approach to sparse high-dimensional multivariate regression models (Q2304238) (← links)
- Pseudo estimation and variable selection in regression (Q2306244) (← links)
- Bayesian discriminant analysis using a high dimensional predictor (Q2316972) (← links)
- Multivariate Gaussian network structure learning (Q2317263) (← links)
- Loss function, unbiasedness, and optimality of Gaussian graphical model selection (Q2317292) (← links)
- Graphical models for zero-inflated single cell gene expression (Q2318662) (← links)
- Multiclass analysis and prediction with network structured covariates (Q2325271) (← links)
- Spectral analysis of high-dimensional time series (Q2326992) (← links)
- Property testing in high-dimensional Ising models (Q2328049) (← links)
- Selection of sparse vine copulas in high dimensions with the Lasso (Q2329765) (← links)
- Sparsistency and agnostic inference in sparse PCA (Q2338928) (← links)
- High-dimensional Ising model selection with Bayesian information criteria (Q2340871) (← links)
- On model selection consistency of regularized M-estimators (Q2340872) (← links)
- Estimation of positive definite \(M\)-matrices and structure learning for attractive Gaussian Markov random fields (Q2341885) (← links)
- Preconditioning the Lasso for sign consistency (Q2346526) (← links)
- Sparse learning via Boolean relaxations (Q2349117) (← links)
- Inferring gene-gene interactions and functional modules using sparse canonical correlation analysis (Q2349574) (← links)
- Goodness-of-fit tests for high-dimensional Gaussian linear models (Q2380086) (← links)
- Simultaneous analysis of Lasso and Dantzig selector (Q2388978) (← links)
- A Bayesian approach to sparse dynamic network identification (Q2391442) (← links)
- A note on the asymptotic distribution of lasso estimator for correlated data (Q2392488) (← links)
- Causal statistical inference in high dimensions (Q2392815) (← links)
- Nonnegative elastic net and application in index tracking (Q2396496) (← links)
