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2307.15677
Cited By
Adversarial training for tabular data with attack propagation
28 July 2023
Tiago Leon Melo
Joao Bravo
Marco O. P. Sampaio
Paolo Romano
Hugo Ferreira
João Tiago Ascensão
P. Bizarro
AAML
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Papers citing
"Adversarial training for tabular data with attack propagation"
10 / 10 papers shown
Title
Why do tree-based models still outperform deep learning on tabular data?
Léo Grinsztajn
Edouard Oyallon
Gaël Varoquaux
LMTD
87
369
0
18 Jul 2022
A Survey of Adversarial Defences and Robustness in NLP
Shreyansh Goyal
Sumanth Doddapaneni
Mitesh M.Khapra
B. Ravindran
AAML
77
30
0
12 Mar 2022
Adversarial Attacks for Tabular Data: Application to Fraud Detection and Imbalanced Data
F. Cartella
Orlando Anunciação
Yuki Funabiki
D. Yamaguchi
Toru Akishita
Olivier Elshocht
AAML
111
78
0
20 Jan 2021
PermuteAttack: Counterfactual Explanation of Machine Learning Credit Scorecards
Masoud Hashemi
Ali Fathi
AAML
67
32
0
24 Aug 2020
HopSkipJumpAttack: A Query-Efficient Decision-Based Attack
Jianbo Chen
Michael I. Jordan
Martin J. Wainwright
AAML
104
670
0
03 Apr 2019
Robustness May Be at Odds with Accuracy
Dimitris Tsipras
Shibani Santurkar
Logan Engstrom
Alexander Turner
Aleksander Madry
AAML
110
1,784
0
30 May 2018
Towards Deep Learning Models Resistant to Adversarial Attacks
Aleksander Madry
Aleksandar Makelov
Ludwig Schmidt
Dimitris Tsipras
Adrian Vladu
SILM
OOD
319
12,151
0
19 Jun 2017
Towards Evaluating the Robustness of Neural Networks
Nicholas Carlini
D. Wagner
OOD
AAML
282
8,587
0
16 Aug 2016
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAML
GAN
282
19,129
0
20 Dec 2014
Intriguing properties of neural networks
Christian Szegedy
Wojciech Zaremba
Ilya Sutskever
Joan Bruna
D. Erhan
Ian Goodfellow
Rob Fergus
AAML
289
14,968
1
21 Dec 2013
1