The following pages link to (Q4864293):
Displaying 50 items.
- Tuning parameter selection for the adaptive LASSO in the autoregressive model (Q526980) (← links)
- Dimensionality reduction by feature clustering for regression problems (Q528696) (← links)
- Regression analysis of locality preserving projections via sparse penalty (Q528758) (← links)
- Convergence of fixed-point continuation algorithms for matrix rank minimization (Q535287) (← links)
- Surveying and comparing simultaneous sparse approximation (or group-lasso) algorithms (Q537241) (← links)
- Non-crossing large-margin probability estimation and its application to robust SVM via pre\-condi\-tion\-ing (Q537462) (← links)
- A statistical analysis of multiple temperature proxies: are reconstructions of surface temperatures over the last 1000 years reliable? (Q542450) (← links)
- Improved variable selection with forward-lasso adaptive shrinkage (Q542500) (← links)
- Random lasso (Q542508) (← links)
- Remembering Leo Breiman (Q542912) (← links)
- Node harvest (Q542973) (← links)
- Sparse modeling of categorial explanatory variables (Q542985) (← links)
- Fixed point and Bregman iterative methods for matrix rank minimization (Q543413) (← links)
- A non-adapted sparse approximation of PDEs with stochastic inputs (Q543721) (← links)
- Randomization of data acquisition and \(\ell_{1}\)-optimization (recognition with compression) (Q544714) (← links)
- Row-column designs with minimal units (Q546105) (← links)
- Simultaneous variable selection for heteroscedastic regression models (Q547385) (← links)
- Estimation of (near) low-rank matrices with noise and high-dimensional scaling (Q548547) (← links)
- Performance guarantees for individualized treatment rules (Q548554) (← links)
- Consistent tuning parameter selection in high dimensional sparse linear regression (Q548648) (← links)
- Semi-varying coefficient models with a diverging number of components (Q548651) (← links)
- Concentration estimates for learning with \(\ell ^{1}\)-regularizer and data dependent hypothesis spaces (Q550498) (← links)
- Sparse variational analysis of linear mixed models for large data sets (Q553008) (← links)
- Bayesian robot system identification with input and output noise (Q553249) (← links)
- Adaptive algorithms for sparse system identification (Q553728) (← links)
- A Bayesian lasso via reversible-jump MCMC (Q553732) (← links)
- Learning gradients on manifolds (Q605040) (← links)
- Model and variable selection procedures for semiparametric time series regression (Q609678) (← links)
- Two-step version of fixed point continuation method for sparse reconstruction (Q610726) (← links)
- Subset selection for vector autoregressive processes via adaptive Lasso (Q613145) (← links)
- Variable selection and regression analysis for graph-structured covariates with an application to genomics (Q614169) (← links)
- Sparse logistic principal components analysis for binary data (Q614179) (← links)
- \(\ell_{1}\)-penalization for mixture regression models (Q619141) (← links)
- Network-based sparse Bayesian classification (Q621090) (← links)
- Penalized least squares for single index models (Q622428) (← links)
- Bayesian variable selection via particle stochastic search (Q625019) (← links)
- Stable direction recovery in single-index models with a diverging number of predictors (Q625784) (← links)
- A random model approach for the LASSO (Q626202) (← links)
- Bayesian model-based tight clustering for time course data (Q626248) (← links)
- Penalized multimodal mixture logit model (Q626262) (← links)
- Consistent group selection in high-dimensional linear regression (Q627307) (← links)
- Saddlepoint condition on a predictor to reconfirm the need for the assumption of a prior distribution (Q629143) (← links)
- Adaptive Dantzig density estimation (Q629798) (← links)
- Exact optimization for the \(\ell ^{1}\)-compressive sensing problem using a modified Dantzig-Wolfe method (Q630594) (← links)
- Autoregressive process modeling via the Lasso procedure (Q631620) (← links)
- A link-free method for testing the significance of predictors (Q631622) (← links)
- On verifiable sufficient conditions for sparse signal recovery via \(\ell_{1}\) minimization (Q633105) (← links)
- Projected gradient iteration for nonlinear operator equation (Q633958) (← links)
- Cox regression analysis in presence of collinearity: an application to assessment of health risks associated with occupational radiation exposure (Q636123) (← links)
- A computational framework for empirical Bayes inference (Q637982) (← links)
