The following pages link to (Q4864293):
Displaying 50 items.
- Enhancing the lasso approach for developing a survival prediction model based on gene expression data (Q308770) (← links)
- The use of vector bootstrapping to improve variable selection precision in Lasso models (Q309418) (← links)
- The benefit of group sparsity in group inference with de-biased scaled group Lasso (Q309547) (← links)
- Screening-based Bregman divergence estimation with NP-dimensionality (Q309558) (← links)
- Thresholding least-squares inference in high-dimensional regression models (Q309566) (← links)
- Designing penalty functions in high dimensional problems: the role of tuning parameters (Q309586) (← links)
- Geometric inference for general high-dimensional linear inverse problems (Q309721) (← links)
- Random subspace method for high-dimensional regression with the \texttt{R} package \texttt{regRSM} (Q311298) (← links)
- Smoothing combined generalized estimating equations in quantile partially linear additive models with longitudinal data (Q311324) (← links)
- Oracle inequalities, variable selection and uniform inference in high-dimensional correlated random effects panel data models (Q311643) (← links)
- Testing a single regression coefficient in high dimensional linear models (Q311657) (← links)
- Parameter estimation for a generalized semiparametric model with repeated measurements (Q312586) (← links)
- A dual method for minimizing a nonsmooth objective over one smooth inequality constraint (Q312667) (← links)
- A rank-corrected procedure for matrix completion with fixed basis coefficients (Q312678) (← links)
- A Bayesian graphical model for genome-wide association studies (GWAS) (Q312923) (← links)
- Detecting abrupt changes in the spectra of high-energy astrophysical sources (Q312981) (← links)
- Empirical likelihood test for high-dimensional two-sample model (Q313106) (← links)
- AIC for the Lasso in generalized linear models (Q315399) (← links)
- Using reinforcement learning to find an optimal set of features (Q316296) (← links)
- DC approximation approaches for sparse optimization (Q319281) (← links)
- Mixed integer second-order cone programming formulations for variable selection in linear regression (Q320071) (← links)
- Demand forecasting with high dimensional data: the case of SKU retail sales forecasting with intra- and inter-category promotional information (Q320919) (← links)
- Latent variable selection in structural equation models (Q321933) (← links)
- Variable selection for additive partial linear quantile regression with missing covariates (Q321935) (← links)
- Sparse and robust normal and \(t\)-portfolios by penalized \(L_q\)-likelihood minimization (Q322443) (← links)
- A posterior probability approach for gene regulatory network inference in genetic perturbation data (Q326558) (← links)
- The adaptive LASSO spline estimation of single-index model (Q328835) (← links)
- Asymtotics of Dantzig selector for a general single-index model (Q328839) (← links)
- Sharp MSE bounds for proximal denoising (Q330102) (← links)
- Fast and scalable Lasso via stochastic Frank-Wolfe methods with a convergence guarantee (Q331671) (← links)
- Sparse topical analysis of dyadic data using matrix tri-factorization (Q331699) (← links)
- PBoostGA: pseudo-boosting genetic algorithm for variable ranking and selection (Q333348) (← links)
- Minimizing variable selection criteria by Markov chain Monte Carlo (Q333351) (← links)
- Automatic variable selection for longitudinal generalized linear models (Q333718) (← links)
- Automatic variable selection for varying coefficient models with longitudinal data (Q334006) (← links)
- Split Bregman algorithms for sparse group lasso with application to MRI reconstruction (Q335981) (← links)
- \(rs\)-sparse principal component analysis: a mixed integer nonlinear programming approach with VNS (Q337243) (← links)
- Multi-step virtual metrology for semiconductor manufacturing: a multilevel and regularization methods-based approach (Q337315) (← links)
- Recipes for sparse LDA of horizontal data (Q339883) (← links)
- Mean and quantile boosting for partially linear additive models (Q340847) (← links)
- Improved nearest neighbor classifiers by weighting and selection of predictors (Q340856) (← links)
- Extensions of stability selection using subsamples of observations and covariates (Q340859) (← links)
- High dimensional robust M-estimation: asymptotic variance via approximate message passing (Q343797) (← links)
- Sparse normalized subband adaptive filter algorithm with \(l_0\)-norm constraint (Q344704) (← links)
- Practical inexact proximal quasi-Newton method with global complexity analysis (Q344963) (← links)
- Selection of polynomial chaos bases via Bayesian model uncertainty methods with applications to sparse approximation of PDEs with stochastic inputs (Q348681) (← links)
- Stable multi-label boosting for image annotation with structural feature selection (Q351013) (← links)
- A novel method for the identification of synchronization effects in multichannel ECoG with an application to epilepsy (Q353892) (← links)
- Strong consistency of Lasso estimators (Q354203) (← links)
- Optimal equivariant prediction for high-dimensional linear models with arbitrary predictor covariance (Q358878) (← links)
