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Concise Explanations of Neural Networks using Adversarial Training

Concise Explanations of Neural Networks using Adversarial Training

15 October 2018
P. Chalasani
Jiefeng Chen
Aravind Sadagopan
S. Jha
Xi Wu
    AAML
    FAtt
ArXivPDFHTML

Papers citing "Concise Explanations of Neural Networks using Adversarial Training"

12 / 12 papers shown
Title
Adversarial Examples Are Not Bugs, They Are Features
Adversarial Examples Are Not Bugs, They Are Features
Andrew Ilyas
Shibani Santurkar
Dimitris Tsipras
Logan Engstrom
Brandon Tran
Aleksander Madry
SILM
89
1,839
0
06 May 2019
Robustness May Be at Odds with Accuracy
Robustness May Be at Odds with Accuracy
Dimitris Tsipras
Shibani Santurkar
Logan Engstrom
Alexander Turner
Aleksander Madry
AAML
99
1,778
0
30 May 2018
Adversarially Robust Generalization Requires More Data
Adversarially Robust Generalization Requires More Data
Ludwig Schmidt
Shibani Santurkar
Dimitris Tsipras
Kunal Talwar
Aleksander Madry
OOD
AAML
131
790
0
30 Apr 2018
A Survey Of Methods For Explaining Black Box Models
A Survey Of Methods For Explaining Black Box Models
Riccardo Guidotti
A. Monreale
Salvatore Ruggieri
Franco Turini
D. Pedreschi
F. Giannotti
XAI
124
3,957
0
06 Feb 2018
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning
  Algorithms
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
Han Xiao
Kashif Rasul
Roland Vollgraf
280
8,878
0
25 Aug 2017
Evasion Attacks against Machine Learning at Test Time
Evasion Attacks against Machine Learning at Test Time
Battista Biggio
Igino Corona
Davide Maiorca
B. Nelson
Nedim Srndic
Pavel Laskov
Giorgio Giacinto
Fabio Roli
AAML
155
2,149
0
21 Aug 2017
Towards Deep Learning Models Resistant to Adversarial Attacks
Towards Deep Learning Models Resistant to Adversarial Attacks
Aleksander Madry
Aleksandar Makelov
Ludwig Schmidt
Dimitris Tsipras
Adrian Vladu
SILM
OOD
301
12,063
0
19 Jun 2017
Regularizing deep networks using efficient layerwise adversarial
  training
Regularizing deep networks using efficient layerwise adversarial training
S. Sankaranarayanan
Arpit Jain
Rama Chellappa
Ser Nam Lim
AAML
54
97
0
22 May 2017
Axiomatic Attribution for Deep Networks
Axiomatic Attribution for Deep Networks
Mukund Sundararajan
Ankur Taly
Qiqi Yan
OOD
FAtt
179
5,986
0
04 Mar 2017
Adversarial Machine Learning at Scale
Adversarial Machine Learning at Scale
Alexey Kurakin
Ian Goodfellow
Samy Bengio
AAML
469
3,140
0
04 Nov 2016
Deep Inside Convolutional Networks: Visualising Image Classification
  Models and Saliency Maps
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps
Karen Simonyan
Andrea Vedaldi
Andrew Zisserman
FAtt
309
7,292
0
20 Dec 2013
Towards Ultrahigh Dimensional Feature Selection for Big Data
Towards Ultrahigh Dimensional Feature Selection for Big Data
Mingkui Tan
Ivor W. Tsang
Li Wang
124
154
0
24 Sep 2012
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