Improving Group Lasso for high-dimensional categorical data

25 October 2022

Papers citing "Improving Group Lasso for high-dimensional categorical data"

9 / 9 papers shown

Title
Trees-Based Models for Correlated Data Assaf Rabinowicz Saharon Rosset 16 7 0 16 Feb 2021
Modelling High-Dimensional Categorical Data Using Nonconvex Fusion Penalties B. Stokell Rajen Dinesh Shah Robert Tibshirani 62 17 0 28 Feb 2020
Bayesian Effect Fusion for Categorical Predictors Daniela Pauger Helga Wagner 35 23 0 29 Mar 2017
Oracle inequalities for the lasso in the Cox model Jian Huang Tingni Sun Z. Ying Yibin Yu Cun-Hui Zhang 83 125 0 20 Jun 2013
Group descent algorithms for nonconvex penalized linear and logistic regression models with grouped predictors P. Breheny Jian Huang 178 287 0 10 Sep 2012
A General Theory of Concave Regularization for High Dimensional Sparse Estimation Problems Cun-Hui Zhang Tong Zhang 190 341 0 25 Aug 2011
Consistent group selection in high-dimensional linear regression Fengrong Wei Jian Huang 198 145 0 29 Nov 2010
Oracle Inequalities and Optimal Inference under Group Sparsity Karim Lounici Massimiliano Pontil Alexandre B. Tsybakov Sara van de Geer 285 382 0 11 Jul 2010
On the conditions used to prove oracle results for the Lasso Sara van de Geer Peter Buhlmann 272 732 0 05 Oct 2009