Cover Image

Univariate-Guided Interaction Modeling

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Echarghaoui, Aymen, Tibshirani, Robert
Format:	Preprint
Published:	2025
Subjects:	Methodology 62J07
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Univariate-Guided Sparse Regression
by: Chatterjee, Sourav, et al.
Published: (2025)

Bayesian Global-Local Shrinkage with Univariate Guidance for Ultra-High-Dimensional Regression
by: Das, Priyam
Published: (2026)

Aggregated Sure Independence Screening for Variable Selection with Interaction Structures
by: Zhang, Tonglin
Published: (2024)

Selection of Ultrahigh-Dimensional Interactions Using $L_0$ Penalty
by: Zhang, Tonglin
Published: (2024)

Factor Augmented Quantile Regression Model
by: Wei, Xiaoyang, et al.
Published: (2025)

Subbagging Variable Selection for Big Data
by: Li, Xian, et al.
Published: (2025)

Model selection by cross-validation in an expectile linear regression
by: Bousselmi, Bilel, et al.
Published: (2026)

The Efficient Shrinkage Path: Maximum Likelihood of Minimum MSE Risk
by: Obenchain, Robert L.
Published: (2021)

Variable Fusion and Selection via a Spike-and-Slab Approach with Nonlocal Priors
by: Miyake, Junya, et al.
Published: (2026)

Estimating the False Discovery Rate of Variable Selection
by: Luo, Yixiang, et al.
Published: (2024)

The Generalized Elastic Net for least squares regression with network-aligned signal and correlated design
by: Tran, Huy, et al.
Published: (2022)

Robust Penalized Estimators for High--Dimensional Generalized Linear Models
by: Valdora, Marina, et al.
Published: (2023)

Penalized KLIC Model Selection for the Generalized Method of Moments in Longitudinal Data with Time-Dependent Covariates
by: Hasan, Mahmud, et al.
Published: (2026)

Sparse twoblock dimension reduction for simultaneous compression and variable selection in two blocks of variables
by: Serneels, Sven
Published: (2024)

A Weibull Mixture Cure Frailty Model for High-dimensional Covariates
by: Kızılaslan, Fatih, et al.
Published: (2024)

Cross Validation for Correlated Data in Regression and Classification Models, with Applications to Deep Learning
by: Yuval, Oren, et al.
Published: (2025)

Variable screening using factor analysis for high-dimensional data with multicollinearity
by: Tanaka, Shuntaro, et al.
Published: (2023)

Structure and Sensitivity in Differential Privacy: Comparing K-Norm Mechanisms
by: Awan, Jordan, et al.
Published: (2018)

Collapsing Categories for Regression with Mixed Predictors
by: Song, Chaegeun, et al.
Published: (2025)

Efficient Sparse Least Absolute Deviation Regression with Differential Privacy
by: Liu, Weidong, et al.
Published: (2024)

Univariate-Guided Sparse Regression for Biobank-Scale High-Dimensional Omics Data
by: Richland, Joshua, et al.
Published: (2025)

Unsupervised Variable Selection for Ultrahigh-Dimensional Clustering Analysis
by: Zhang, Tonglin, et al.
Published: (2024)

Optimal shrinkage estimation in heteroscedastic hierarchical linear models
by: Kou, Samuel, et al.
Published: (2015)

Data-driven configuration tuning of glmnet for balancing accuracy and computational efficiency
by: Muroya, Shuhei, et al.
Published: (2026)

A New Formula for Faster Computation of the K-Fold Cross-Validation and Good Regularisation Parameter Values in Ridge Regression
by: Liland, Kristian Hovde, et al.
Published: (2022)

Regularization and Selection in A Directed Network Model with Nodal Homophily and Nodal Effects
by: Xing, Zhaoyu, et al.
Published: (2025)

Air-HOLP: Adaptive Regularized Feature Screening for High Dimensional Correlated Data
by: Joudah, Ibrahim, et al.
Published: (2024)

Substantive-Model-Compatible Multiple Imputation for Cox Regression with a Diverging Number of Covariates
by: Zhang, Zhilin, et al.
Published: (2026)

A Statistical-Modelling Approach to Feedforward Neural Network Model Selection
by: McInerney, Andrew, et al.
Published: (2022)

Bayesian inference with sources of uncertainty: from confidence modelling to sparse estimation
by: Rosa, Rafael Mouallem, et al.
Published: (2026)

Unbiased Regression-Adjusted Estimation of Average Treatment Effects in Randomized Controlled Trials
by: Abadie, Alberto, et al.
Published: (2025)

Projection predictive variable selection for discrete response families with finite support
by: Weber, Frank, et al.
Published: (2023)

Testing-driven Variable Selection in Bayesian Modal Regression
by: Duan, Jiasong, et al.
Published: (2025)

$\ell_1$-Regularized Generalized Least Squares
by: Nobari, Kaveh S., et al.
Published: (2024)

Pseudo-Labeling for Kernel Ridge Regression under Covariate Shift
by: Wang, Kaizheng
Published: (2023)

Mixed Semi-Supervised Generalized-Linear-Regression with Applications to Deep-Learning and Interpolators
by: Yuval, Oren, et al.
Published: (2023)

Maximum smoothed likelihood method for the combination of multiple diagnostic tests, with application to the ROC estimation
by: Zheng, Fangyong, et al.
Published: (2026)

Right-censored models by the expectile method
by: Ciuperca, Gabriela
Published: (2024)

Sparse estimation in ordinary kriging for functional data
by: Matsui, Hidetoshi, et al.
Published: (2023)

A method for sparse and robust independent component analysis
by: Heinonen, Lauri, et al.
Published: (2025)