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Provable Robustness of ReLU networks via Maximization of Linear Regions

Provable Robustness of ReLU networks via Maximization of Linear Regions

17 October 2018
Francesco Croce
Maksym Andriushchenko
Matthias Hein
ArXivPDFHTML

Papers citing "Provable Robustness of ReLU networks via Maximization of Linear Regions"

42 / 42 papers shown
Title
When Deep Learning Meets Polyhedral Theory: A Survey
When Deep Learning Meets Polyhedral Theory: A Survey
Joey Huchette
Gonzalo Muñoz
Thiago Serra
Calvin Tsay
AI4CE
96
33
0
29 Apr 2023
Confidence-aware Training of Smoothed Classifiers for Certified
  Robustness
Confidence-aware Training of Smoothed Classifiers for Certified Robustness
Jongheon Jeong
Seojin Kim
Jinwoo Shin
AAML
21
7
0
18 Dec 2022
Reliable Robustness Evaluation via Automatically Constructed Attack
  Ensembles
Reliable Robustness Evaluation via Automatically Constructed Attack Ensembles
Shengcai Liu
Fu Peng
Jiaheng Zhang
AAML
39
11
0
23 Nov 2022
Towards Robust Dataset Learning
Towards Robust Dataset Learning
Yihan Wu
Xinda Li
Florian Kerschbaum
Heng Huang
Hongyang R. Zhang
DD
OOD
49
10
0
19 Nov 2022
Improved techniques for deterministic l2 robustness
Improved techniques for deterministic l2 robustness
Sahil Singla
S. Feizi
AAML
25
10
0
15 Nov 2022
Robust Binary Models by Pruning Randomly-initialized Networks
Robust Binary Models by Pruning Randomly-initialized Networks
Chen Liu
Ziqi Zhao
Sabine Süsstrunk
Mathieu Salzmann
TPM
AAML
MQ
32
4
0
03 Feb 2022
The Fundamental Limits of Interval Arithmetic for Neural Networks
The Fundamental Limits of Interval Arithmetic for Neural Networks
M. Mirman
Maximilian Baader
Martin Vechev
32
6
0
09 Dec 2021
How and When Adversarial Robustness Transfers in Knowledge Distillation?
How and When Adversarial Robustness Transfers in Knowledge Distillation?
Rulin Shao
Ming Zhou
C. Bezemer
Cho-Jui Hsieh
AAML
32
17
0
22 Oct 2021
How to Certify Machine Learning Based Safety-critical Systems? A
  Systematic Literature Review
How to Certify Machine Learning Based Safety-critical Systems? A Systematic Literature Review
Florian Tambon
Gabriel Laberge
Le An
Amin Nikanjam
Paulina Stevia Nouwou Mindom
Y. Pequignot
Foutse Khomh
G. Antoniol
E. Merlo
François Laviolette
37
66
0
26 Jul 2021
Adversarial Robustness via Fisher-Rao Regularization
Adversarial Robustness via Fisher-Rao Regularization
Marine Picot
Francisco Messina
Malik Boudiaf
Fabrice Labeau
Ismail Ben Ayed
Pablo Piantanida
AAML
31
23
0
12 Jun 2021
Relating Adversarially Robust Generalization to Flat Minima
Relating Adversarially Robust Generalization to Flat Minima
David Stutz
Matthias Hein
Bernt Schiele
OOD
38
65
0
09 Apr 2021
On the Adversarial Robustness of Vision Transformers
On the Adversarial Robustness of Vision Transformers
Rulin Shao
Zhouxing Shi
Jinfeng Yi
Pin-Yu Chen
Cho-Jui Hsieh
ViT
33
138
0
29 Mar 2021
Robust Models Are More Interpretable Because Attributions Look Normal
Robust Models Are More Interpretable Because Attributions Look Normal
Zifan Wang
Matt Fredrikson
Anupam Datta
OOD
FAtt
35
25
0
20 Mar 2021
Towards Evaluating the Robustness of Deep Diagnostic Models by
  Adversarial Attack
Towards Evaluating the Robustness of Deep Diagnostic Models by Adversarial Attack
Mengting Xu
Tao Zhang
Zhongnian Li
Mingxia Liu
Daoqiang Zhang
AAML
OOD
MedIm
33
41
0
05 Mar 2021
Globally-Robust Neural Networks
Globally-Robust Neural Networks
Klas Leino
Zifan Wang
Matt Fredrikson
AAML
OOD
80
126
0
16 Feb 2021
Adversarial Robustness of Stabilized NeuralODEs Might be from Obfuscated
  Gradients
Adversarial Robustness of Stabilized NeuralODEs Might be from Obfuscated Gradients
Yifei Huang
Yaodong Yu
Hongyang R. Zhang
Yi Ma
Yuan Yao
AAML
37
26
0
28 Sep 2020
SoK: Certified Robustness for Deep Neural Networks
SoK: Certified Robustness for Deep Neural Networks
Linyi Li
Tao Xie
Bo-wen Li
AAML
33
128
0
09 Sep 2020
On the Loss Landscape of Adversarial Training: Identifying Challenges
  and How to Overcome Them
On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them
Chen Liu
Mathieu Salzmann
Tao R. Lin
Ryota Tomioka
Sabine Süsstrunk
AAML
24
81
0
15 Jun 2020
ReLU Code Space: A Basis for Rating Network Quality Besides Accuracy
ReLU Code Space: A Basis for Rating Network Quality Besides Accuracy
Natalia Shepeleva
Werner Zellinger
Michal Lewandowski
Bernhard A. Moser
25
3
0
20 May 2020
Adversarial Robustness on In- and Out-Distribution Improves
  Explainability
Adversarial Robustness on In- and Out-Distribution Improves Explainability
Maximilian Augustin
Alexander Meinke
Matthias Hein
OOD
75
99
0
20 Mar 2020
Topological Effects on Attacks Against Vertex Classification
Topological Effects on Attacks Against Vertex Classification
B. A. Miller
Mustafa Çamurcu
Alexander J. Gomez
Kevin S. Chan
Tina Eliassi-Rad
AAML
19
2
0
12 Mar 2020
Overfitting in adversarially robust deep learning
Overfitting in adversarially robust deep learning
Leslie Rice
Eric Wong
Zico Kolter
47
787
0
26 Feb 2020
Fast is better than free: Revisiting adversarial training
Fast is better than free: Revisiting adversarial training
Eric Wong
Leslie Rice
J. Zico Kolter
AAML
OOD
99
1,159
0
12 Jan 2020
The Threat of Adversarial Attacks on Machine Learning in Network
  Security -- A Survey
The Threat of Adversarial Attacks on Machine Learning in Network Security -- A Survey
Olakunle Ibitoye
Rana Abou-Khamis
Mohamed el Shehaby
Ashraf Matrawy
M. O. Shafiq
AAML
37
68
0
06 Nov 2019
Test-Time Training with Self-Supervision for Generalization under
  Distribution Shifts
Test-Time Training with Self-Supervision for Generalization under Distribution Shifts
Yu Sun
Xiaolong Wang
Zhuang Liu
John Miller
Alexei A. Efros
Moritz Hardt
TTA
OOD
27
92
0
29 Sep 2019
Padé Activation Units: End-to-end Learning of Flexible Activation
  Functions in Deep Networks
Padé Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks
Alejandro Molina
P. Schramowski
Kristian Kersting
ODL
23
79
0
15 Jul 2019
Certifiable Robustness and Robust Training for Graph Convolutional
  Networks
Certifiable Robustness and Robust Training for Graph Convolutional Networks
Daniel Zügner
Stephan Günnemann
OffRL
39
162
0
28 Jun 2019
Provably Robust Deep Learning via Adversarially Trained Smoothed
  Classifiers
Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers
Hadi Salman
Greg Yang
Jungshian Li
Pengchuan Zhang
Huan Zhang
Ilya P. Razenshteyn
Sébastien Bubeck
AAML
45
536
0
09 Jun 2019
Provably Robust Boosted Decision Stumps and Trees against Adversarial
  Attacks
Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks
Maksym Andriushchenko
Matthias Hein
28
61
0
08 Jun 2019
Robustness for Non-Parametric Classification: A Generic Attack and
  Defense
Robustness for Non-Parametric Classification: A Generic Attack and Defense
Yao-Yuan Yang
Cyrus Rashtchian
Yizhen Wang
Kamalika Chaudhuri
SILM
AAML
34
42
0
07 Jun 2019
Securing Connected & Autonomous Vehicles: Challenges Posed by
  Adversarial Machine Learning and The Way Forward
Securing Connected & Autonomous Vehicles: Challenges Posed by Adversarial Machine Learning and The Way Forward
A. Qayyum
Muhammad Usama
Junaid Qadir
Ala I. Al-Fuqaha
AAML
27
187
0
29 May 2019
Thwarting finite difference adversarial attacks with output
  randomization
Thwarting finite difference adversarial attacks with output randomization
Haidar Khan
Daniel Park
Azer Khan
B. Yener
SILM
AAML
38
0
0
23 May 2019
Scaling up the randomized gradient-free adversarial attack reveals
  overestimation of robustness using established attacks
Scaling up the randomized gradient-free adversarial attack reveals overestimation of robustness using established attacks
Francesco Croce
Jonas Rauber
Matthias Hein
AAML
20
30
0
27 Mar 2019
Provable Certificates for Adversarial Examples: Fitting a Ball in the
  Union of Polytopes
Provable Certificates for Adversarial Examples: Fitting a Ball in the Union of Polytopes
Matt Jordan
Justin Lewis
A. Dimakis
AAML
24
57
0
20 Mar 2019
Wasserstein Adversarial Examples via Projected Sinkhorn Iterations
Wasserstein Adversarial Examples via Projected Sinkhorn Iterations
Eric Wong
Frank R. Schmidt
J. Zico Kolter
AAML
36
210
0
21 Feb 2019
Certified Adversarial Robustness via Randomized Smoothing
Certified Adversarial Robustness via Randomized Smoothing
Jeremy M. Cohen
Elan Rosenfeld
J. Zico Kolter
AAML
22
1,998
0
08 Feb 2019
MMA Training: Direct Input Space Margin Maximization through Adversarial
  Training
MMA Training: Direct Input Space Margin Maximization through Adversarial Training
G. Ding
Yash Sharma
Kry Yik-Chau Lui
Ruitong Huang
AAML
27
270
0
06 Dec 2018
Prototype-based Neural Network Layers: Incorporating Vector Quantization
Prototype-based Neural Network Layers: Incorporating Vector Quantization
S. Saralajew
Lars Holdijk
Maike Rees
T. Villmann
MQ
25
15
0
04 Dec 2018
Logit Pairing Methods Can Fool Gradient-Based Attacks
Logit Pairing Methods Can Fool Gradient-Based Attacks
Marius Mosbach
Maksym Andriushchenko
T. A. Trost
Matthias Hein
Dietrich Klakow
AAML
33
82
0
29 Oct 2018
Empirical Bounds on Linear Regions of Deep Rectifier Networks
Empirical Bounds on Linear Regions of Deep Rectifier Networks
Thiago Serra
Srikumar Ramalingam
8
42
0
08 Oct 2018
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Guy Katz
Clark W. Barrett
D. Dill
Kyle D. Julian
Mykel Kochenderfer
AAML
249
1,842
0
03 Feb 2017
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
326
5,847
0
08 Jul 2016
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