Cover Image

Strong Screening Rules for Group-based SLOPE Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Feser, Fabio, Evangelou, Marina
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Dual Feature Reduction for the Sparse-group Lasso and its Adaptive Variant
by: Feser, Fabio, et al.
Published: (2024)

Safe Screening Rules for Group SLOPE
by: Bao, Runxue, et al.
Published: (2025)

Logistic Variational Bayes Revisited
by: Komodromos, Michael, et al.
Published: (2024)

The Strong Screening Rule for SLOPE
by: Larsson, Johan, et al.
Published: (2020)

A Gaussian Process Model for Ordinal Data with Applications to Chemoinformatics
by: Gosnell, Arron, et al.
Published: (2024)

Sharp Trade-Offs in High-Dimensional Inference via 2-Level SLOPE
by: Bu, Zhiqi, et al.
Published: (2025)

A Set of Rules for Model Validation
by: Camacho, José
Published: (2025)

TabPFN: One Model to Rule Them All?
by: Zhang, Qiong, et al.
Published: (2025)

Federated Rule Ensemble Method in Medical Data
by: Wan, Ke, et al.
Published: (2026)

Group Spike and Slab Variational Bayes
by: Komodromos, Michael, et al.
Published: (2023)

Building Trees for Probabilistic Prediction via Scoring Rules
by: Shashaani, Sara, et al.
Published: (2024)

Screening for Diabetes Mellitus in the U.S. Population Using Neural Network Models and Complex Survey Designs
by: Matabuena, Marcos, et al.
Published: (2024)

Iterative Methods for Vecchia-Laplace Approximations for Latent Gaussian Process Models
by: Kündig, Pascal, et al.
Published: (2023)

CURLS: Causal Rule Learning for Subgroups with Significant Treatment Effect
by: Zhou, Jiehui, et al.
Published: (2024)

Choice of Scoring Rules for Indirect Elicitation of Properties with Parametric Assumptions
by: Hu, Lingfang, et al.
Published: (2025)

Scalable Krylov Subspace Methods for Generalized Mixed-Effects Models with Crossed Random Effects
by: Kündig, Pascal, et al.
Published: (2025)

Causal Rule Ensemble: Interpretable Discovery and Inference of Heterogeneous Treatment Effects
by: Bargagli-Stoffi, Falco J., et al.
Published: (2020)

Neyman Meets Causal Machine Learning: Experimental Evaluation of Individualized Treatment Rules
by: Li, Michael Lingzhi, et al.
Published: (2024)

Robust Inference Methods for Latent Group Panel Models under Possible Group Non-Separation
by: Akgun, Oguzhan, et al.
Published: (2025)

A New Causal Rule Learning Approach to Interpretable Estimation of Heterogeneous Treatment Effect
by: Wu, Ying, et al.
Published: (2023)

Approximate Gibbs Sampler for Efficient Inference of Hierarchical Bayesian Models for Grouped Count Data
by: Yu, Jin-Zhu, et al.
Published: (2022)

Efficient Budget Allocation for Large-Scale LLM-Enabled Virtual Screening
by: Li, Zaile, et al.
Published: (2024)

Fusing Individualized Treatment Rules Using Secondary Outcomes
by: Gao, Daiqi, et al.
Published: (2024)

Locally Interpretable Individualized Treatment Rules for Black-Box Decision Models
by: Charvadeh, Yasin Khadem, et al.
Published: (2026)

Nonlinear Causal Discovery for Grouped Data
by: Göbler, Konstantin, et al.
Published: (2025)

Interaction Screening and Pseudolikelihood Approaches for Tensor Learning in Ising Models
by: Liu, Tianyu, et al.
Published: (2023)

Group Shapley Value and Counterfactual Simulations in a Structural Model
by: Kwon, Yongchan, et al.
Published: (2024)

Transfer Learning for Classification under Decision Rule Drift with Application to Optimal Individualized Treatment Rule Estimation
by: Wang, Xiaohan, et al.
Published: (2025)

GRASP: Grouped Regression with Adaptive Shrinkage Priors
by: Tew, Shu Yu, et al.
Published: (2025)

Strongly Consistent Community Detection in Popularity Adjusted Block Models
by: Yuan, Quan, et al.
Published: (2025)

Estimation of Optimal Dynamic Treatment Assignment Rules under Policy Constraints
by: Sakaguchi, Shosei
Published: (2021)

Multi-Group Quadratic Discriminant Analysis via Projection
by: Wang, Yuchao, et al.
Published: (2026)

Non-parametric Hypothesis Tests for Distributional Group Symmetry
by: Chiu, Kenny, et al.
Published: (2023)

Asymptotic Theory for Graphical SLOPE: Precision Estimation and Pattern Convergence
by: Hejný, Ivan, et al.
Published: (2026)

Group selection and shrinkage: Structured sparsity for semiparametric additive models
by: Thompson, Ryan, et al.
Published: (2021)

Geometric-Based Pruning Rules For Change Point Detection in Multiple Independent Time Series
by: Pishchagina, Liudmila, et al.
Published: (2023)

Structured Conformal Inference for Matrix Completion with Applications to Group Recommender Systems
by: Liang, Ziyi, et al.
Published: (2024)

Spectral Clustering with Variance Information for Group Structure Estimation in Panel Data
by: Yu, Lu, et al.
Published: (2022)

Gaussian Process Boosting
by: Sigrist, Fabio
Published: (2020)

Structural Causality-based Generalizable Concept Discovery Models
by: Sinha, Sanchit, et al.
Published: (2024)