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Variable Selection

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Showing 301–350 of 566 papers

TitleStatusHype
Fast leave-one-cluster-out cross-validation using clustered Network Information Criterion (NICc)—0
Fast Multi-Class Probabilistic Classifier by Sparse Non-parametric Density Estimation—0
Fast Saddle-Point Algorithm for Generalized Dantzig Selector and FDR Control with the Ordered l1-Norm—0
Forward variable selection enables fast and accurate dynamic system identification with Karhunen-Loève decomposed Gaussian processes—0
Feature and Variable Selection in Classification—0
Bayesian forecast combination using time-varying features—0
Feature selection in functional data classification with recursive maxima hunting—0
Feature Selection through Minimization of the VC dimension—0
Federated Automatic Latent Variable Selection in Multi-output Gaussian Processes—0
Federated Data Analytics: A Study on Linear Models—0
Federated Sufficient Dimension Reduction Through High-Dimensional Sparse Sliced Inverse Regression—0
Flexible co-data learning for high-dimensional prediction—0
Flexible shrinkage in high-dimensional Bayesian spatial autoregressive models—0
Fractional Naive Bayes (FNB): non-convex optimization for a parsimonious weighted selective naive Bayes classifier—0
Fréchet regression with implicit denoising and multicollinearity reduction—0
Functional Integrative Bayesian Analysis of High-dimensional Multiplatform Genomic Data—0
Fuzzy clustering of distribution-valued data using adaptive L2 Wasserstein distances—0
GAM(L)A: An econometric model for interpretable Machine Learning—0
Generalization Guarantees for Learning Branch-and-Cut Policies in Integer Programming—0
Generalized Sparse Additive Model with Unknown Link Function—0
Global sensitivity analysis for optimization with variable selection—0
Glucose values prediction five years ahead with a new framework of missing responses in reproducing kernel Hilbert spaces, and the use of continuous glucose monitoring technology—0
Gradient-based kernel method for feature extraction and variable selection—0
Gradient Boosting for Spatial Regression Models with Autoregressive Disturbances—0
Greedy Active Learning Algorithm for Logistic Regression Models—0
Group descent algorithms for nonconvex penalized linear and logistic regression models with grouped predictors—0
Grouped Orthogonal Matching Pursuit for Variable Selection and Prediction—0
Grouping effects of sparse CCA models in variable selection—0
Group Regularized Estimation under Structural Hierarchy—0
Group Sparse Additive Machine—0
Group-sparse SVD Models and Their Applications in Biological Data—0
Harnessing the Potential of Volatility: Advancing GDP Prediction—0
Heterogeneous Exposures to Systematic and Idiosyncratic Risk across Crypto Assets: A Divide-and-Conquer Approach—0
Heteroscedastic Double Bayesian Elastic Net—0
High Dimensional Bayesian Optimization with Kernel Principal Component Analysis—0
High Dimensional Binary Choice Model with Unknown Heteroskedasticity or Instrumental Variables—0
High-dimensional Ordinary Least-squares Projection for Screening Variables—0
High-Dimensional Screening Using Multiple Grouping of Variables—0
High dimensional Sparse Gaussian Graphical Mixture Model—0
High dimensional thresholded regression and shrinkage effect—0
Hybrid Reinforcement Learning Framework for Mixed-Variable Problems—0
Hyperspectral-Multispectral Image Fusion with Weighted LASSO—0
Identifying Genetic Risk Factors via Sparse Group Lasso with Group Graph Structure—0
Identifying relevant positions in proteins by Critical Variable Selection—0
Identifying spatial interdependence in panel data with large N and small T—0
Impact of novel aggregation methods for flexible, time-sensitive EHR prediction without variable selection or cleaning—0
Improved joint modelling of breast cancer radiomics features and hazard by image registration aided longitudinal CT data—0
Improving Gibbs Sampler Scan Quality with DoGS—0
Improving probability selecting based weights for Satisfiability Problem—0
Improving the Predictive Performances of k Nearest Neighbors Learning by Efficient Variable Selection—0
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