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Variable Selection

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Showing 351–400 of 566 papers

TitleStatusHype
Inference in High Dimensions with the Penalized Score Test—0
Inference of Multiscale Gaussian Graphical Model—0
Information-theoretic limits of Bayesian network structure learning—0
Instance Explainable Temporal Network For Multivariate Timeseries—0
Instrumenting an SMT Solver to Solve Hybrid Network Reachability Problems—0
International Trade Flow Prediction with Bilateral Trade Provisions—0
Interpretable Machine Learning Models for Modal Split Prediction in Transportation Systems—0
Interpretable random forest models through forward variable selection—0
Interpreting Outliers: Localized Logistic Regression for Density Ratio Estimation—0
Iterative Reweighted Framework Based Algorithms for Sparse Linear Regression with Generalized Elastic Net Penalty—0
Joint Estimation of Precision Matrices in Heterogeneous Populations—0
kNN Algorithm for Conditional Mean and Variance Estimation with Automated Uncertainty Quantification and Variable Selection—0
Knockoff-Inspired Feature Selection via Generative Models—0
Knockoffs Inference under Privacy Constraints—0
Knoop: Practical Enhancement of Knockoff with Over-Parameterization for Variable Selection—0
Large-scale Nonlinear Variable Selection via Kernel Random Features—0
LASSO-Driven Inference in Time and Space—0
Latent Simplex Position Model: High Dimensional Multi-view Clustering with Uncertainty Quantification—0
Learning to Branch—0
Learning to Branch in Combinatorial Optimization with Graph Pointer Networks—0
Least Angle Regression in Tangent Space and LASSO for Generalized Linear Models—0
LocalGLMnet: interpretable deep learning for tabular data—0
Local Interpretable Model-agnostic Explanations of Bayesian Predictive Models via Kullback-Leibler Projections—0
Local White Matter Architecture Defines Functional Brain Dynamics—0
Lookback for Learning to Branch—0
Mathematics of Digital Twins and Transfer Learning for PDE Models—0
MDA for random forests: inconsistency, and a practical solution via the Sobol-MDA—0
Mean field variational Bayesian inference for support vector machine classification—0
Measuring the Algorithmic Convergence of Randomized Ensembles: The Regression Setting—0
MEBoost: Variable Selection in the Presence of Measurement Error—0
Median Selection Subset Aggregation for Parallel Inference—0
Missing Value Knockoffs—0
Mitigating Bias in Online Microfinance Platforms: A Case Study on Kiva.org—0
Mixture model for designs in high dimensional regression and the LASSO—0
MM Algorithms for Distance Covariance based Sufficient Dimension Reduction and Sufficient Variable Selection—0
MM for Penalized Estimation—0
When stakes are high: balancing accuracy and transparency with Model-Agnostic Interpretable Data-driven suRRogates—0
Model-independent variable selection via the rule-based variable priority—0
Monte Carlo Simulation for Lasso-Type Problems by Estimator Augmentation—0
Selecting Diverse Models for Scientific Insight—0
Multi-task Additive Models for Robust Estimation and Automatic Structure Discovery—0
Multivariate Bernoulli distribution—0
Multivariate Dyadic Regression Trees for Sparse Learning Problems—0
Nearest Neighbour Based Estimates of Gradients: Sharp Nonasymptotic Bounds and Applications—0
Nearly Optimal Variational Inference for High Dimensional Regression with Shrinkage Priors—0
Netboost: Boosting-supported network analysis improves high-dimensional omics prediction in acute myeloid leukemia and Huntington's disease—0
Neural lasso: a unifying approach of lasso and neural networks—0
Noise-Augmented Privacy-Preserving Empirical Risk Minimization with Dual-purpose Regularizer and Privacy Budget Retrieval and Recycling—0
Stochastic Zeroth-order Discretizations of Langevin Diffusions for Bayesian Inference—0
Nonlinear Permuted Granger Causality—0
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