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Variable Selection

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Showing 151–200 of 566 papers

TitleStatusHype
Variable-Complexity Weighted-Tempered Gibbs Samplers for Bayesian Variable Selection—0
Sequential Knockoffs for Variable Selection in Reinforcement Learning—0
An ADMM approach for multi-response regression with overlapping groups and interaction effects—0
A Survey of Numerical Algorithms that can Solve the Lasso Problems—0
Environment Invariant Linear Least SquaresCode0
Variable Selection for Kernel Two-Sample Tests—0
Convergence of uncertainty estimates in Ensemble and Bayesian sparse model discovery—0
Asymptotic Inference for Multi-Stage Stationary Treatment Policy with Variable SelectionCode0
Federated Sufficient Dimension Reduction Through High-Dimensional Sparse Sliced Inverse Regression—0
Evaluation of the potential of Near Infrared Hyperspectral Imaging for monitoring the invasive brown marmorated stink bug—0
Dual-sPLS: a family of Dual Sparse Partial Least Squares regressions for feature selection and prediction with tunable sparsity; evaluation on simulated and near-infrared (NIR) dataCode0
Understanding Best Subset Selection: A Tale of Two C(omplex)ities—0
Bayesian Models of Functional Connectomics and Behavior—0
On High dimensional Poisson models with measurement error: hypothesis testing for nonlinear nonconvex optimization—0
Functional Integrative Bayesian Analysis of High-dimensional Multiplatform Genomic Data—0
A machine learning framework for neighbor generation in metaheuristic search—0
Multi-Task Learning for Sparsity Pattern Heterogeneity: Statistical and Computational PerspectivesCode0
Applications of Machine Learning for the Ratemaking in Agricultural Insurances—0
Can Machine Learning discover the determining factors in participation in insurance schemes? A comparative analysis—0
Stable Learning via Sparse Variable Independence—0
Variable selection for nonlinear Cox regression model via deep learning—0
Transfer learning for tensor Gaussian graphical models—0
The Best Path Algorithm automatic variables selection via High Dimensional Graphical Models—0
RFFNet: Large-Scale Interpretable Kernel Methods via Random Fourier FeaturesCode0
Online Linearized LASSO—0
Near-optimal multiple testing in Bayesian linear models with finite-sample FDR controlCode0
Improving the Predictive Performances of k Nearest Neighbors Learning by Efficient Variable Selection—0
Bayesian Sparse Regression for Mixed Multi-Responses with Application to Runtime Metrics Prediction in Fog Manufacturing—0
Experts in the Loop: Conditional Variable Selection for Accelerating Post-Silicon Analysis Based on Deep Learning—0
Sparse high-dimensional linear regression with a partitioned empirical Bayes ECM algorithm—0
Copula Entropy based Variable Selection for Survival AnalysisCode0
Two-Stage Robust and Sparse Distributed Statistical Inference for Large-Scale Data—0
Branch Ranking for Efficient Mixed-Integer Programming via Offline Ranking-based Policy Learning—0
Sparse Bayesian State-Space and Time-Varying Parameter Models—0
Energy Trees: Regression and Classification With Structured and Mixed-Type Covariates—0
A Statistical-Modelling Approach to Feedforward Neural Network Model Selection—0
Conditional Variable Selection for Intelligent Test—0
Lookback for Learning to Branch—0
Federated Data Analytics: A Study on Linear Models—0
Deep Reinforcement Learning for Exact Combinatorial Optimization: Learning to Branch—0
Sparse-group boosting -- Unbiased group and variable selectionCode0
Robust Knockoffs for Controlling False Discoveries With an Application to Bond Recovery Rates—0
Forecasting macroeconomic data with Bayesian VARs: Sparse or dense? It depends!Code0
Forward variable selection enables fast and accurate dynamic system identification with Karhunen-Loève decomposed Gaussian processes—0
ecpc: An R-package for generic co-data models for high-dimensional prediction—0
Determination of class-specific variables in nonparametric multiple-class classification—0
High Dimensional Bayesian Optimization with Kernel Principal Component Analysis—0
Wind power predictions from nowcasts to 4-hour forecasts: a learning approach with variable selection—0
Adaptive Noisy Data Augmentation for Regularized Estimation and Inference in Generalized Linear Models—0
Towards a Unified Framework for Uncertainty-aware Nonlinear Variable Selection with Theoretical Guarantees—0
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