Pages that link to "Item:Q3631444"

The following pages link to The Group Lasso for Logistic Regression (Q3631444):

Displaying 50 items.

• Crossing time windows optimization based on mutual information for hybrid BCI (Q2092188) (← links)
• High dimensional generalized linear models for temporal dependent data (Q2108473) (← links)
• Regression with adaptive Lasso and correlation based penalty (Q2109879) (← links)
• Penalized polygram regression (Q2111959) (← links)
• Linear convergence of prox-SVRG method for separable non-smooth convex optimization problems under bounded metric subregularity (Q2115253) (← links)
• Posterior contraction in group sparse logit models for categorical responses (Q2123271) (← links)
• Bayesian group selection with non-local priors (Q2135854) (← links)
• GSDAR: a fast Newton algorithm for \(\ell_0\) regularized generalized linear models with statistical guarantee (Q2135875) (← links)
• The robust nearest shrunken centroids classifier for high-dimensional heavy-tailed data (Q2154953) (← links)
• A data-driven line search rule for support recovery in high-dimensional data analysis (Q2157522) (← links)
• Robust grouped variable selection using distributionally robust optimization (Q2159460) (← links)
• Grouped feature importance and combined features effect plot (Q2172623) (← links)
• Variable selection for sparse logistic regression (Q2202033) (← links)
• Regression and subgroup detection for heterogeneous samples (Q2228234) (← links)
• Fully asynchronous stochastic coordinate descent: a tight lower bound on the parallelism achieving linear speedup (Q2235160) (← links)
• On the stability and generalization of neural networks with VC dimension and fuzzy feature encoders (Q2235467) (← links)
• Multinomial logit models with implicit variable selection (Q2256779) (← links)
• Bridge regression: adaptivity and group selection (Q2276183) (← links)
• Classification tree algorithm for grouped variables (Q2282589) (← links)
• Fuzzy Lasso regression model with exact explanatory variables and fuzzy responses (Q2302823) (← links)
• AIC for the group Lasso in generalized linear models (Q2303501) (← links)
• Informative gene selection for microarray classification via adaptive elastic net with conditional mutual information (Q2310656) (← links)
• Accelerated alternating direction method of multipliers: an optimal \(O(1 / K)\) nonergodic analysis (Q2311982) (← links)
• Estimation bounds and sharp oracle inequalities of regularized procedures with Lipschitz loss functions (Q2313281) (← links)
• Non-concave penalization in linear mixed-effect models and regularized selection of fixed effects (Q2316730) (← links)
• Adaptively weighted group Lasso for semiparametric quantile regression models (Q2325373) (← links)
• High-dimensional generalized linear models incorporating graphical structure among predictors (Q2326055) (← links)
• Nonparametric additive beta regression for fractional response with application to body fat data (Q2329907) (← links)
• Optimization problems involving group sparsity terms (Q2330642) (← links)
• A two-step fixed-point proximity algorithm for a class of non-differentiable optimization models in machine learning (Q2333729) (← links)
• Lasso-type penalization in the framework of generalized additive models for location, scale and shape (Q2337322) (← links)
• Rating scales as predictors -- the old question of scale level and some answers (Q2339059) (← links)
• A penalty approach to differential item functioning in Rasch models (Q2348182) (← links)
• Sparse high-dimensional varying coefficient model: nonasymptotic minimax study (Q2352741) (← links)
• Linearized alternating direction method with parallel splitting and adaptive penalty for separable convex programs in machine learning (Q2353007) (← links)
• A group VISA algorithm for variable selection (Q2353367) (← links)
• Parallel block coordinate minimization with application to group regularized regression (Q2358088) (← links)
• On the impact of model selection on predictor identification and parameter inference (Q2358941) (← links)
• Group variable selection and estimation in the Tobit censored response model (Q2361224) (← links)
• Simultaneous analysis of Lasso and Dantzig selector (Q2388978) (← links)
• Efficient block-coordinate descent algorithms for the group Lasso (Q2392933) (← links)
• IPF-LASSO: integrative \(L_1\)-penalized regression with penalty factors for prediction based on multi-omics data (Q2405418) (← links)
• The degrees of freedom of partly smooth regularizers (Q2409395) (← links)
• Globally sparse and locally dense signal recovery for compressed sensing (Q2410784) (← links)
• Quantile regression with group Lasso for classification (Q2418274) (← links)
• A uniform framework for the combination of penalties in generalized structured models (Q2418291) (← links)
• Logistic biplot for nominal data (Q2418308) (← links)
• PAC-Bayesian risk bounds for group-analysis sparse regression by exponential weighting (Q2418515) (← links)
• Graph-based sparse linear discriminant analysis for high-dimensional classification (Q2418517) (← links)
• A random block-coordinate Douglas-Rachford splitting method with low computational complexity for binary logistic regression (Q2419533) (← links)