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Parseval Networks: Improving Robustness to Adversarial Examples
v1v2 (latest)

Parseval Networks: Improving Robustness to Adversarial Examples

28 April 2017
Moustapha Cissé
Piotr Bojanowski
Edouard Grave
Yann N. Dauphin
Nicolas Usunier
    AAML
ArXiv (abs)PDFHTML

Papers citing "Parseval Networks: Improving Robustness to Adversarial Examples"

50 / 489 papers shown
Title
Adversarial Examples on Object Recognition: A Comprehensive Survey
Adversarial Examples on Object Recognition: A Comprehensive Survey
A. Serban
E. Poll
Joost Visser
AAML
118
73
0
07 Aug 2020
Improve Generalization and Robustness of Neural Networks via Weight
  Scale Shifting Invariant Regularizations
Improve Generalization and Robustness of Neural Networks via Weight Scale Shifting Invariant Regularizations
Ziquan Liu
Yufei Cui
Antoni B. Chan
122
13
0
07 Aug 2020
Hardware Accelerator for Adversarial Attacks on Deep Learning Neural
  Networks
Hardware Accelerator for Adversarial Attacks on Deep Learning Neural Networks
Haoqiang Guo
Lu Peng
Jian Zhang
Fang Qi
Lide Duan
AAML
47
6
0
03 Aug 2020
How benign is benign overfitting?
How benign is benign overfitting?
Amartya Sanyal
P. Dokania
Varun Kanade
Philip Torr
NoLaAAML
89
58
0
08 Jul 2020
Fast Training of Deep Neural Networks Robust to Adversarial
  Perturbations
Fast Training of Deep Neural Networks Robust to Adversarial Perturbations
Justin A. Goodwin
Olivia M. Brown
Victoria Helus
OODAAML
27
3
0
08 Jul 2020
Robust Learning with Frequency Domain Regularization
Robust Learning with Frequency Domain Regularization
Weiyu Guo
Yidong Ouyang
AAML
36
2
0
07 Jul 2020
On Connections between Regularizations for Improving DNN Robustness
On Connections between Regularizations for Improving DNN Robustness
Yiwen Guo
Long Chen
Yurong Chen
Changshui Zhang
AAML
51
14
0
04 Jul 2020
Efficient Proximal Mapping of the 1-path-norm of Shallow Networks
Efficient Proximal Mapping of the 1-path-norm of Shallow Networks
Fabian Latorre
Paul Rolland
Nadav Hallak
Volkan Cevher
AAML
67
4
0
02 Jul 2020
Opportunities and Challenges in Deep Learning Adversarial Robustness: A
  Survey
Opportunities and Challenges in Deep Learning Adversarial Robustness: A Survey
S. Silva
Peyman Najafirad
AAMLOOD
106
135
0
01 Jul 2020
Deep Isometric Learning for Visual Recognition
Deep Isometric Learning for Visual Recognition
Haozhi Qi
Chong You
Xinyu Wang
Yi-An Ma
Jitendra Malik
VLM
102
55
0
30 Jun 2020
Lipschitzness Is All You Need To Tame Off-policy Generative Adversarial
  Imitation Learning
Lipschitzness Is All You Need To Tame Off-policy Generative Adversarial Imitation Learning
Lionel Blondé
Pablo Strasser
Alexandros Kalousis
90
22
0
28 Jun 2020
A general framework for defining and optimizing robustness
A general framework for defining and optimizing robustness
Alessandro Tibo
M. Jaeger
Kim G. Larsen
22
0
0
19 Jun 2020
Model-Aware Regularization For Learning Approaches To Inverse Problems
Model-Aware Regularization For Learning Approaches To Inverse Problems
Jaweria Amjad
Zhaoyang Lyu
M. Rodrigues
MedIm
18
0
0
18 Jun 2020
Globally Injective ReLU Networks
Globally Injective ReLU Networks
Michael Puthawala
K. Kothari
Matti Lassas
Ivan Dokmanić
Maarten V. de Hoop
103
28
0
15 Jun 2020
On Lipschitz Regularization of Convolutional Layers using Toeplitz
  Matrix Theory
On Lipschitz Regularization of Convolutional Layers using Toeplitz Matrix Theory
Alexandre Araujo
Benjamin Négrevergne
Y. Chevaleyre
Jamal Atif
47
0
0
15 Jun 2020
On Saliency Maps and Adversarial Robustness
On Saliency Maps and Adversarial Robustness
Puneet Mangla
Vedant Singh
V. Balasubramanian
AAML
47
17
0
14 Jun 2020
Rethinking Clustering for Robustness
Rethinking Clustering for Robustness
Motasem Alfarra
Juan C. Pérez
Adel Bibi
Ali K. Thabet
Pablo Arbelaez
Guohao Li
OOD
41
0
0
13 Jun 2020
Achieving robustness in classification using optimal transport with
  hinge regularization
Achieving robustness in classification using optimal transport with hinge regularization
M. Serrurier
Franck Mamalet
Alberto González Sanz
Thibaut Boissin
Jean-Michel Loubes
E. del Barrio
AAML
58
40
0
11 Jun 2020
Towards an Intrinsic Definition of Robustness for a Classifier
Towards an Intrinsic Definition of Robustness for a Classifier
Théo Giraudon
Vincent Gripon
Matthias Löwe
Franck Vermet
OODAAML
25
2
0
09 Jun 2020
The Lipschitz Constant of Self-Attention
The Lipschitz Constant of Self-Attention
Hyunjik Kim
George Papamakarios
A. Mnih
96
146
0
08 Jun 2020
All your loss are belong to Bayes
All your loss are belong to Bayes
Christian J. Walder
Richard Nock
61
5
0
08 Jun 2020
Distributional Robustness with IPMs and links to Regularization and GANs
Distributional Robustness with IPMs and links to Regularization and GANs
Hisham Husain
70
22
0
08 Jun 2020
Rethinking Empirical Evaluation of Adversarial Robustness Using
  First-Order Attack Methods
Rethinking Empirical Evaluation of Adversarial Robustness Using First-Order Attack Methods
Kyungmi Lee
A. Chandrakasan
ELMAAML
69
3
0
01 Jun 2020
Quantized Neural Networks: Characterization and Holistic Optimization
Quantized Neural Networks: Characterization and Holistic Optimization
Yoonho Boo
Sungho Shin
Wonyong Sung
MQ
78
8
0
31 May 2020
Exploring Model Robustness with Adaptive Networks and Improved
  Adversarial Training
Exploring Model Robustness with Adaptive Networks and Improved Adversarial Training
Zheng Xu
Ali Shafahi
Tom Goldstein
AAML
51
2
0
30 May 2020
Calibrated Surrogate Losses for Adversarially Robust Classification
Calibrated Surrogate Losses for Adversarially Robust Classification
Han Bao
Clayton Scott
Masashi Sugiyama
78
46
0
28 May 2020
Model-Based Robust Deep Learning: Generalizing to Natural,
  Out-of-Distribution Data
Model-Based Robust Deep Learning: Generalizing to Natural, Out-of-Distribution Data
Alexander Robey
Hamed Hassani
George J. Pappas
OOD
103
43
0
20 May 2020
Cross-Lingual Low-Resource Set-to-Description Retrieval for Global
  E-Commerce
Cross-Lingual Low-Resource Set-to-Description Retrieval for Global E-Commerce
Juntao Li
Chang Liu
Jian Wang
Lidong Bing
Hongsong Li
Xiaozhong Liu
Dongyan Zhao
Rui Yan
46
12
0
17 May 2020
Lifted Regression/Reconstruction Networks
Lifted Regression/Reconstruction Networks
R. Høier
Christopher Zach
31
7
0
07 May 2020
Training robust neural networks using Lipschitz bounds
Training robust neural networks using Lipschitz bounds
Patricia Pauli
Anne Koch
J. Berberich
Paul Kohler
Frank Allgöwer
90
163
0
06 May 2020
CWY Parametrization: a Solution for Parallelized Optimization of
  Orthogonal and Stiefel Matrices
CWY Parametrization: a Solution for Parallelized Optimization of Orthogonal and Stiefel Matrices
Valerii Likhosherstov
Jared Davis
K. Choromanski
Adrian Weller
38
4
0
18 Apr 2020
On Adversarial Examples and Stealth Attacks in Artificial Intelligence
  Systems
On Adversarial Examples and Stealth Attacks in Artificial Intelligence Systems
I. Tyukin
D. Higham
A. Gorban
AAML
46
39
0
09 Apr 2020
Controllable Orthogonalization in Training DNNs
Controllable Orthogonalization in Training DNNs
Lei Huang
Li Liu
Fan Zhu
Diwen Wan
Zehuan Yuan
Bo Li
Ling Shao
87
44
0
02 Apr 2020
Dataless Model Selection with the Deep Frame Potential
Dataless Model Selection with the Deep Frame Potential
Calvin Murdock
Simon Lucey
84
6
0
30 Mar 2020
What Deep CNNs Benefit from Global Covariance Pooling: An Optimization
  Perspective
What Deep CNNs Benefit from Global Covariance Pooling: An Optimization Perspective
Qilong Wang
Li Zhang
Banggu Wu
Dongwei Ren
P. Li
W. Zuo
Q. Hu
75
21
0
25 Mar 2020
Defense Through Diverse Directions
Defense Through Diverse Directions
Christopher M. Bender
Yang Li
Yifeng Shi
Michael K. Reiter
Junier B. Oliva
AAML
51
4
0
24 Mar 2020
Double Backpropagation for Training Autoencoders against Adversarial
  Attack
Double Backpropagation for Training Autoencoders against Adversarial Attack
Chengjin Sun
Sizhe Chen
Xiaolin Huang
SILMAAML
81
5
0
04 Mar 2020
Exactly Computing the Local Lipschitz Constant of ReLU Networks
Exactly Computing the Local Lipschitz Constant of ReLU Networks
Matt Jordan
A. Dimakis
92
112
0
02 Mar 2020
Improving Robustness of Deep-Learning-Based Image Reconstruction
Improving Robustness of Deep-Learning-Based Image Reconstruction
Ankit Raj
Y. Bresler
Yue Liu
OODAAML
96
51
0
26 Feb 2020
Attacks Which Do Not Kill Training Make Adversarial Learning Stronger
Attacks Which Do Not Kill Training Make Adversarial Learning Stronger
Jingfeng Zhang
Xilie Xu
Bo Han
Gang Niu
Li-zhen Cui
Masashi Sugiyama
Mohan S. Kankanhalli
AAML
62
406
0
26 Feb 2020
Gradient $\ell_1$ Regularization for Quantization Robustness
Gradient ℓ1\ell_1ℓ1​ Regularization for Quantization Robustness
Milad Alizadeh
Arash Behboodi
M. V. Baalen
Christos Louizos
Tijmen Blankevoort
Max Welling
MQ
58
8
0
18 Feb 2020
Deflecting Adversarial Attacks
Deflecting Adversarial Attacks
Yao Qin
Nicholas Frosst
Colin Raffel
G. Cottrell
Geoffrey E. Hinton
AAML
64
15
0
18 Feb 2020
ResiliNet: Failure-Resilient Inference in Distributed Neural Networks
ResiliNet: Failure-Resilient Inference in Distributed Neural Networks
Ashkan Yousefpour
Brian Q. Nguyen
Siddartha Devic
Guanhua Wang
Aboudy Kreidieh
Hans Lobel
Alexandre M. Bayen
J. Jue
48
2
0
18 Feb 2020
Regularized Training and Tight Certification for Randomized Smoothed
  Classifier with Provable Robustness
Regularized Training and Tight Certification for Randomized Smoothed Classifier with Provable Robustness
Huijie Feng
Chunpeng Wu
Guoyang Chen
Weifeng Zhang
Y. Ning
AAML
71
11
0
17 Feb 2020
Generalised Lipschitz Regularisation Equals Distributional Robustness
Generalised Lipschitz Regularisation Equals Distributional Robustness
Zac Cranko
Zhan Shi
Xinhua Zhang
Richard Nock
Simon Kornblith
OOD
86
21
0
11 Feb 2020
Understanding the Decision Boundary of Deep Neural Networks: An
  Empirical Study
Understanding the Decision Boundary of Deep Neural Networks: An Empirical Study
David Mickisch
F. Assion
Florens Greßner
W. Günther
M. Motta
AAML
69
34
0
05 Feb 2020
Efficient Riemannian Optimization on the Stiefel Manifold via the Cayley
  Transform
Efficient Riemannian Optimization on the Stiefel Manifold via the Cayley Transform
Jun Li
Fuxin Li
S. Todorovic
89
107
0
04 Feb 2020
REST: Robust and Efficient Neural Networks for Sleep Monitoring in the
  Wild
REST: Robust and Efficient Neural Networks for Sleep Monitoring in the Wild
Rahul Duggal
Scott Freitas
Cao Xiao
Duen Horng Chau
Jimeng Sun
127
22
0
29 Jan 2020
PaRoT: A Practical Framework for Robust Deep Neural Network Training
PaRoT: A Practical Framework for Robust Deep Neural Network Training
Edward W. Ayers
Francisco Eiras
Majd Hawasly
I. Whiteside
OOD
97
19
0
07 Jan 2020
ATHENA: A Framework based on Diverse Weak Defenses for Building
  Adversarial Defense
ATHENA: A Framework based on Diverse Weak Defenses for Building Adversarial Defense
Meng
Jianhai Su
Jason M. O'Kane
Pooyan Jamshidi
AAML
57
7
0
02 Jan 2020
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