Don't Fall for Tuning Parameters: Tuning-Free Variable Selection in High Dimensions With the TREX

2 April 2014

Papers citing "Don't Fall for Tuning Parameters: Tuning-Free Variable Selection in High Dimensions With the TREX"

11 / 11 papers shown

Title
Optimal tuning-free convex relaxation for noisy matrix completion Yuepeng Yang Cong Ma 28 8 0 12 Jul 2022
A Survey of Tuning Parameter Selection for High-dimensional Regression Y. Wu Lan Wang 48 35 0 10 Aug 2019
Stability selection enables robust learning of partial differential equations from limited noisy data Suryanarayana Maddu B. Cheeseman I. Sbalzarini Christian L. Müller 18 20 0 17 Jul 2019
Fast, Parameter free Outlier Identification for Robust PCA V. Menon Sheetal Kalyani 33 2 0 13 Apr 2018
Inference for high-dimensional instrumental variables regression David Gold Johannes Lederer Jing Tao 30 37 0 18 Aug 2017
Generalized Concomitant Multi-Task Lasso for sparse multimodal regression Mathurin Massias Olivier Fercoq Alexandre Gramfort Joseph Salmon 51 23 0 27 May 2017
Balancing Statistical and Computational Precision: A General Theory and Applications to Sparse Regression Mahsa Taheri Néhémy Lim Johannes Lederer 33 3 0 23 Sep 2016
Oracle Inequalities for High-dimensional Prediction Johannes Lederer Lu Yu Irina Gaynanova 34 24 0 01 Aug 2016
Non-convex Global Minimization and False Discovery Rate Control for the TREX Jacob Bien Irina Gaynanova Johannes Lederer Christian L. Müller 17 22 0 22 Apr 2016
Optimal Two-Step Prediction in Regression Didier Chételat Johannes Lederer Joseph Salmon 42 19 0 18 Oct 2014
Sparse and compositionally robust inference of microbial ecological networks Zachary D. Kurtz Christian L. Müller Emily R. Miraldi D. Littman M. Blaser Richard Bonneau 37 1,226 0 18 Aug 2014