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Don't Fall for Tuning Parameters: Tuning-Free Variable Selection in High
  Dimensions With the TREX
v1v2v3 (latest)

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

2 April 2014
Johannes Lederer
Christian L. Müller
ArXiv (abs)PDFHTML

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

15 / 15 papers shown
Title
The generalized hyperbolic family and automatic model selection through
  the multiple-choice LASSO
The generalized hyperbolic family and automatic model selection through the multiple-choice LASSO
L. Bagnato
A. Farcomeni
A. Punzo
25
3
0
14 Jun 2023
Tuning-free ridge estimators for high-dimensional generalized linear
  models
Tuning-free ridge estimators for high-dimensional generalized linear models
Shih-Ting Huang
Fang Xie
Johannes Lederer
35
4
0
27 Feb 2020
A Survey of Tuning Parameter Selection for High-dimensional Regression
A Survey of Tuning Parameter Selection for High-dimensional Regression
Y. Wu
Lan Wang
77
36
0
10 Aug 2019
Stability selection enables robust learning of partial differential
  equations from limited noisy data
Stability selection enables robust learning of partial differential equations from limited noisy data
Suryanarayana Maddu
B. Cheeseman
I. Sbalzarini
Christian L. Müller
58
19
0
17 Jul 2019
Structured and Unstructured Outlier Identification for Robust PCA: A Non
  iterative, Parameter free Algorithm
Structured and Unstructured Outlier Identification for Robust PCA: A Non iterative, Parameter free Algorithm
V. Menon
Sheetal Kalyani
51
16
0
11 Sep 2018
Fast, Parameter free Outlier Identification for Robust PCA
Fast, Parameter free Outlier Identification for Robust PCA
V. Menon
Sheetal Kalyani
66
2
0
13 Apr 2018
Inference for high-dimensional instrumental variables regression
Inference for high-dimensional instrumental variables regression
David Gold
Johannes Lederer
Jing Tao
89
36
0
18 Aug 2017
Generalized Concomitant Multi-Task Lasso for sparse multimodal
  regression
Generalized Concomitant Multi-Task Lasso for sparse multimodal regression
Mathurin Massias
Olivier Fercoq
Alexandre Gramfort
Joseph Salmon
84
23
0
27 May 2017
Balancing Statistical and Computational Precision: A General Theory and
  Applications to Sparse Regression
Balancing Statistical and Computational Precision: A General Theory and Applications to Sparse Regression
Mahsa Taheri
Néhémy Lim
Johannes Lederer
68
4
0
23 Sep 2016
Oracle Inequalities for High-dimensional Prediction
Oracle Inequalities for High-dimensional Prediction
Johannes Lederer
Lu Yu
Irina Gaynanova
110
24
0
01 Aug 2016
Non-convex Global Minimization and False Discovery Rate Control for the
  TREX
Non-convex Global Minimization and False Discovery Rate Control for the TREX
Jacob Bien
Irina Gaynanova
Johannes Lederer
Christian L. Müller
47
22
0
22 Apr 2016
Topology Adaptive Graph Estimation in High Dimensions
Topology Adaptive Graph Estimation in High Dimensions
Johannes Lederer
Christian L. Müller
49
1
0
27 Oct 2014
Optimal Two-Step Prediction in Regression
Optimal Two-Step Prediction in Regression
Didier Chételat
Johannes Lederer
Joseph Salmon
120
19
0
18 Oct 2014
A Practical Scheme and Fast Algorithm to Tune the Lasso With Optimality
  Guarantees
A Practical Scheme and Fast Algorithm to Tune the Lasso With Optimality Guarantees
M. Chichignoud
Johannes Lederer
Martin J. Wainwright
103
13
0
01 Oct 2014
Sparse and compositionally robust inference of microbial ecological
  networks
Sparse and compositionally robust inference of microbial ecological networks
Zachary D. Kurtz
Christian L. Müller
Emily R. Miraldi
D. Littman
M. Blaser
Richard Bonneau
79
1,253
0
18 Aug 2014
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