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Variable Selection

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TitleStatusHype
Bayesian Approximate Kernel Regression with Variable SelectionCode0
Elastic Net Procedure for Partially Linear Models—0
The mRMR variable selection method: a comparative study for functional data—0
High-dimensional Ordinary Least-squares Projection for Screening Variables—0
On the Computational Complexity of High-Dimensional Bayesian Variable Selection—0
Provable Sparse Tensor Decomposition—0
Accurate Estimation of Quantitative Trait Locus Effects with Epistatic by Improved Variational Linear Regression—0
Equitability of Dependence Measure—0
Breaking the Curse of Dimensionality with Convex Neural Networks—0
Support recovery without incoherence: A case for nonconvex regularization—0
PLUTO: Penalized Unbiased Logistic Regression Trees—0
Optimal variable selection in multi-group sparse discriminant analysis—0
Group Regularized Estimation under Structural Hierarchy—0
Faithful Variable Screening for High-Dimensional Convex Regression—0
Controlling false discoveries in high-dimensional situations: Boosting with stability selection—0
Feature Selection through Minimization of the VC dimension—0
Median Selection Subset Aggregation for Parallel Inference—0
Penalized versus constrained generalized eigenvalue problems—0
Sparse Additive Model using Symmetric Nonnegative Definite Smoothers—0
Efficient Regularized Regression for Variable Selection with L0 Penalty—0
Extensions of stability selection using subsamples of observations and covariates—0
Sequential Advantage Selection for Optimal Treatment Regimes—0
A Permutation Approach for Selecting the Penalty Parameter in Penalized Model Selection—0
Don't Fall for Tuning Parameters: Tuning-Free Variable Selection in High Dimensions With the TREX—0
Selective Factor Extraction in High Dimensions—0
Simultaneous sparse estimation of canonical vectors in the p>>N setting—0
Sparse Quantile Huber Regression for Efficient and Robust Estimation—0
Feature and Variable Selection in Classification—0
Sparse Bayesian Unsupervised Learning—0
Monte Carlo Simulation for Lasso-Type Problems by Estimator Augmentation—0
Inference in High Dimensions with the Penalized Score Test—0
Oracle Inequalities for Convex Loss Functions with Non-Linear Targets—0
bartMachine: Machine Learning with Bayesian Additive Regression Trees—0
Data Mining using Unguided Symbolic Regression on a Blast Furnace Dataset—0
High dimensional Sparse Gaussian Graphical Mixture Model—0
Confidence Sets Based on Thresholding Estimators in High-Dimensional Gaussian Regression Models—0
Optimal Feature Selection in High-Dimensional Discriminant Analysis—0
Randomized maximum-contrast selection: subagging for large-scale regression—0
Mean field variational Bayesian inference for support vector machine classification—0
A Rank Minrelation - Majrelation Coefficient—0
Predictive Correlation Screening: Application to Two-stage Predictor Design in High Dimension—0
Bayesian Compressed Regression—0
Gradient-based kernel method for feature extraction and variable selection—0
APPLE: Approximate Path for Penalized Likelihood Estimators—0
Mixture model for designs in high dimensional regression and the LASSO—0
Group descent algorithms for nonconvex penalized linear and logistic regression models with grouped predictors—0
Consistent selection of tuning parameters via variable selection stability—0
High-Dimensional Screening Using Multiple Grouping of Variables—0
Structured Estimation in Nonparameteric Cox Model—0
Multivariate Bernoulli distribution—0
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