The following pages link to (Q4864293):
Displaying 50 items.
- Least quantile regression via modern optimization (Q482902) (← links)
- CAM: causal additive models, high-dimensional order search and penalized regression (Q482906) (← links)
- Variable selection for BART: an application to gene regulation (Q484051) (← links)
- Selection of spatial-temporal lattice models: assessing the impact of climate conditions on a mountain pine beetle outbreak (Q484694) (← links)
- The horseshoe estimator: posterior concentration around nearly black vectors (Q485913) (← links)
- On estimation and selection of autologistic regression models via penalized pseudolikelihood (Q486061) (← links)
- \(L_1\)-penalization in functional linear regression with subgaussian design (Q487731) (← links)
- Variable selection in quantile regression when the models have autoregressive errors (Q488595) (← links)
- Penalized weighted composite quantile regression in the linear regression model with heavy-tailed autocorrelated errors (Q488598) (← links)
- On the linear convergence of the approximate proximal splitting method for non-smooth convex optimization (Q489108) (← links)
- Bregman iteration algorithm for sparse nonnegative matrix factorizations via alternating \(l_1\)-norm minimization (Q490274) (← links)
- Selecting massive variables using an iterated conditional modes/medians algorithm (Q491389) (← links)
- Normalized and standard Dantzig estimators: two approaches (Q491397) (← links)
- High-dimensional inference in misspecified linear models (Q491406) (← links)
- Computing sparse representation in a highly coherent dictionary based on difference of \(L_1\) and \(L_2\) (Q493283) (← links)
- Expectation propagation in linear regression models with spike-and-slab priors (Q493741) (← links)
- On the residual empirical process based on the ALASSO in high dimensions and its functional oracle property (Q494167) (← links)
- Oracle inequalities for high dimensional vector autoregressions (Q494169) (← links)
- Cross-validation for selecting a model selection procedure (Q494374) (← links)
- Semiparametric model building for regression models with time-varying parameters (Q494386) (← links)
- A flexible semiparametric forecasting model for time series (Q494408) (← links)
- A note on the smoothing quadratic regularization method for non-Lipschitz optimization (Q494677) (← links)
- Toward a unified theory of sparse dimensionality reduction in Euclidean space (Q496171) (← links)
- A half thresholding projection algorithm for sparse solutions of LCPs (Q497459) (← links)
- Variable selection of varying dispersion student-\(t\) regression models (Q498090) (← links)
- Outlier detection and robust mixture modeling using nonconvex penalized likelihood (Q499439) (← links)
- On nonparametric feature filters in electromagnetic imaging (Q499441) (← links)
- Cox process functional learning (Q500875) (← links)
- Supersparse linear integer models for optimized medical scoring systems (Q506427) (← links)
- Accelerating a Gibbs sampler for variable selection on genomics data with summarization and variable pre-selection combining an array DBMS and R (Q506436) (← links)
- Robust feature screening for varying coefficient models via quantile partial correlation (Q506573) (← links)
- Shrinkage estimation of the linear model with spatial interaction (Q506575) (← links)
- Stochastic compositional gradient descent: algorithms for minimizing compositions of expected-value functions (Q507334) (← links)
- MLSLR: multilabel learning via sparse logistic regression (Q507663) (← links)
- Robust estimation and variable selection in censored partially linear additive models (Q508109) (← links)
- Penalized B-spline estimator for regression functions using total variation penalty (Q511676) (← links)
- Auction optimization using regression trees and linear models as integer programs (Q511796) (← links)
- Asymptotic properties of a component-wise ARH(1) plug-in predictor (Q511989) (← links)
- DCA based algorithms for feature selection in multi-class support vector machine (Q513636) (← links)
- Additive model selection (Q513754) (← links)
- GAITA: a Gauss-Seidel iterative thresholding algorithm for \(\ell_q\) regularized least squares regression (Q515771) (← links)
- A two-component \(G\)-prior for variable selection (Q516468) (← links)
- Multiple-population shrinkage estimation via sliced inverse regression (Q517384) (← links)
- Beyond support in two-stage variable selection (Q517395) (← links)
- Decomposition into low-rank plus additive matrices for background/foreground separation: a review for a comparative evaluation with a large-scale dataset (Q518124) (← links)
- Sparse recovery under weak moment assumptions (Q520739) (← links)
- Data based identification and prediction of nonlinear and complex dynamical systems (Q521774) (← links)
- An extragradient-based alternating direction method for convex minimization (Q525598) (← links)
- Penalized least squares estimation with weakly dependent data (Q525888) (← links)
- A generalized eigenvalues classifier with embedded feature selection (Q526414) (← links)
