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Trimming Stability Selection increases variable selection robustness
23 November 2021
Tino Werner
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Papers citing
"Trimming Stability Selection increases variable selection robustness"
9 / 9 papers shown
Title
On the Adversarial Robustness of LASSO Based Feature Selection
Fuwei Li
Lifeng Lai
Shuguang Cui
AAML
57
19
0
20 Oct 2020
Handling cellwise outliers by sparse regression and robust covariance
Jakob Raymaekers
P. Rousseeuw
22
14
0
28 Dec 2019
Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning
Matthew Jagielski
Alina Oprea
Battista Biggio
Chang-rui Liu
Cristina Nita-Rotaru
Yue Liu
AAML
85
763
0
01 Apr 2018
Towards Evaluating the Robustness of Neural Networks
Nicholas Carlini
D. Wagner
OOD
AAML
266
8,579
0
16 Aug 2016
Practical Black-Box Attacks against Machine Learning
Nicolas Papernot
Patrick McDaniel
Ian Goodfellow
S. Jha
Z. Berkay Celik
A. Swami
MLAU
AAML
75
3,682
0
08 Feb 2016
High-dimensional robust precision matrix estimation: Cellwise corruption under
ε
ε
ε
-contamination
Po-Ling Loh
X. Tan
58
31
0
24 Sep 2015
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAML
GAN
280
19,107
0
20 Dec 2014
High-dimensional generalized linear models and the lasso
Sara van de Geer
629
756
0
04 Apr 2008
Piecewise linear regularized solution paths
Saharon Rosset
Ji Zhu
535
522
0
16 Aug 2007
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