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Variable Selection

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Showing 101–150 of 566 papers

TitleStatusHype
Sparse PCA with False Discovery Rate Controlled Variable Selection—0
Semi-Supervised Deep Sobolev Regression: Estimation and Variable Selection by ReQU Neural Network—0
A least distance estimator for a multivariate regression model using deep neural networks—0
Detection of evolutionary shifts in variance under an Ornsten-Uhlenbeck modelCode0
Variable Selection in High Dimensional Linear Regressions with Parameter InstabilityCode0
Random Forest Variable Importance-based Selection Algorithm in Class Imbalance Problem—0
Sparse Learning and Class Probability Estimation with Weighted Support Vector Machines—0
Economic Forecasts Using Many Noises—0
A deep learning pipeline for cross-sectional and longitudinal multiview data integrationCode0
Exact Combinatorial Optimization with Temporo-Attentional Graph Neural Networks—0
Co-data Learning for Bayesian Additive Regression TreesCode0
Data-Driven Bayesian Network Models of Hurricane Evacuation Decision Making—0
High Dimensional Binary Choice Model with Unknown Heteroskedasticity or Instrumental Variables—0
Bayesian Quantile Regression with Subset Selection: A Decision Analysis Perspective—0
Variable Selection in Maximum Mean Discrepancy for Interpretable Distribution Comparison—0
Sparse high-dimensional linear mixed modeling with a partitioned empirical Bayes ECM algorithm—0
Non-parametric Conditional Independence Testing for Mixed Continuous-Categorical Variables: A Novel Method and Numerical EvaluationCode0
The Conditional Prediction Function: A Novel Technique to Control False Discovery Rate for Complex Models—0
Sparse Deep Learning for Time Series Data: Theory and Applications—0
Quantifying predictive uncertainty of aphasia severity in stroke patients with sparse heteroscedastic Bayesian high-dimensional regressionCode0
Effect of hyperparameters on variable selection in random forestsCode0
Identifying spatial interdependence in panel data with large N and small T—0
Neural lasso: a unifying approach of lasso and neural networks—0
Adaptive Lasso, Transfer Lasso, and Beyond: An Asymptotic PerspectiveCode0
Small Area Estimation with Random Forests and the LASSO—0
Systematic reduction of Hyperspectral Images for high-throughput Plastic Characterization—0
Spectral information criterion for automatic elbow detection—0
Nonlinear Permuted Granger Causality—0
Best-Subset Selection in Generalized Linear Models: A Fast and Consistent Algorithm via Splicing Technique—0
An Efficient Shapley Value Computation for the Naive Bayes Classifier—0
VolTS: A Volatility-based Trading System to forecast Stock Markets Trend using Statistics and Machine Learning—0
Stochastic Step-wise Feature Selection for Exponential Random Graph Models (ERGMs)—0
Poverty rate prediction using multi-modal survey and earth observation data—0
Sparse Gaussian Graphical Models with Discrete Optimization: Computational and Statistical Perspectives—0
On Sufficient Graphical Models—0
Multimodal Deep Learning for Personalized Renal Cell Carcinoma Prognosis: Integrating CT Imaging and Clinical DataCode0
Deep Inception Networks: A General End-to-End Framework for Multi-asset Quantitative Strategies—0
Scalable variable selection for two-view learning tasks with projection operatorsCode0
Learning to Branch in Combinatorial Optimization with Graph Pointer Networks—0
Structured Learning in Time-dependent Cox ModelsCode0
Harnessing the Potential of Volatility: Advancing GDP Prediction—0
TreeDQN: Learning to minimize Branch-and-Bound treeCode0
Localized Neural Network Modelling of Time Series: A Case Study on US Monetary Policy—0
Statistical Estimation for Covariance Structures with Tail Estimates using Nodewise Quantile Predictive Regression Models—0
Provable Identifiability of Two-Layer ReLU Neural Networks via LASSO Regularization—0
Sparsifying Bayesian neural networks with latent binary variables and normalizing flowsCode0
Slow Kill for Big Data Learning—0
System Identification with Copula EntropyCode0
The Adaptive τ-Lasso: Robustness and Oracle Properties—0
DiscoVars: A New Data Analysis Perspective -- Application in Variable Selection for Clustering—0
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