ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1704.08847
  4. Cited By
Parseval Networks: Improving Robustness to Adversarial Examples

Parseval Networks: Improving Robustness to Adversarial Examples

28 April 2017
Moustapha Cissé
Piotr Bojanowski
Edouard Grave
Yann N. Dauphin
Nicolas Usunier
    AAML
ArXivPDFHTML

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

50 / 487 papers shown
Title
Improving Sentence Representations with Consensus Maximisation
Improving Sentence Representations with Consensus Maximisation
Shuai Tang
V. D. Sa
SSL
AI4TS
24
4
0
02 Oct 2018
Improved robustness to adversarial examples using Lipschitz regularization of the loss
Chris Finlay
Adam M. Oberman
B. Abbasi
13
34
0
01 Oct 2018
A Kernel Perspective for Regularizing Deep Neural Networks
A Kernel Perspective for Regularizing Deep Neural Networks
A. Bietti
Grégoire Mialon
Dexiong Chen
Julien Mairal
11
15
0
30 Sep 2018
Interpreting Adversarial Robustness: A View from Decision Surface in
  Input Space
Interpreting Adversarial Robustness: A View from Decision Surface in Input Space
Fuxun Yu
Chenchen Liu
Yanzhi Wang
Liang Zhao
Xiang Chen
AAML
OOD
31
27
0
29 Sep 2018
HashTran-DNN: A Framework for Enhancing Robustness of Deep Neural
  Networks against Adversarial Malware Samples
HashTran-DNN: A Framework for Enhancing Robustness of Deep Neural Networks against Adversarial Malware Samples
Deqiang Li
Ramesh Baral
Tao Li
Han Wang
Qianmu Li
Shouhuai Xu
AAML
12
20
0
18 Sep 2018
Adversarial Propagation and Zero-Shot Cross-Lingual Transfer of Word
  Vector Specialization
Adversarial Propagation and Zero-Shot Cross-Lingual Transfer of Word Vector Specialization
E. Ponti
Ivan Vulić
Goran Glavas
N. Mrksic
Anna Korhonen
VLM
20
46
0
11 Sep 2018
Structure-Preserving Transformation: Generating Diverse and Transferable
  Adversarial Examples
Structure-Preserving Transformation: Generating Diverse and Transferable Adversarial Examples
Dan Peng
Zizhan Zheng
Xiaofeng Zhang
AAML
9
5
0
08 Sep 2018
Exploiting Invertible Decoders for Unsupervised Sentence Representation
  Learning
Exploiting Invertible Decoders for Unsupervised Sentence Representation Learning
Shuai Tang
V. D. Sa
SSL
13
1
0
08 Sep 2018
Lipschitz Networks and Distributional Robustness
Lipschitz Networks and Distributional Robustness
Zac Cranko
Simon Kornblith
Zhan Shi
Richard Nock
OOD
8
11
0
04 Sep 2018
Lipschitz regularized Deep Neural Networks generalize and are
  adversarially robust
Lipschitz regularized Deep Neural Networks generalize and are adversarially robust
Chris Finlay
Jeff Calder
Bilal Abbasi
Adam M. Oberman
16
55
0
28 Aug 2018
Unsupervised Multilingual Word Embeddings
Unsupervised Multilingual Word Embeddings
Xilun Chen
Claire Cardie
14
129
0
27 Aug 2018
Adversarial Attacks Against Automatic Speech Recognition Systems via
  Psychoacoustic Hiding
Adversarial Attacks Against Automatic Speech Recognition Systems via Psychoacoustic Hiding
Lea Schonherr
Katharina Kohls
Steffen Zeiler
Thorsten Holz
D. Kolossa
AAML
17
285
0
16 Aug 2018
Is Robustness the Cost of Accuracy? -- A Comprehensive Study on the
  Robustness of 18 Deep Image Classification Models
Is Robustness the Cost of Accuracy? -- A Comprehensive Study on the Robustness of 18 Deep Image Classification Models
D. Su
Huan Zhang
Hongge Chen
Jinfeng Yi
Pin-Yu Chen
Yupeng Gao
VLM
13
387
0
05 Aug 2018
Learning Overparameterized Neural Networks via Stochastic Gradient
  Descent on Structured Data
Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data
Yuanzhi Li
Yingyu Liang
MLT
15
650
0
03 Aug 2018
Rob-GAN: Generator, Discriminator, and Adversarial Attacker
Rob-GAN: Generator, Discriminator, and Adversarial Attacker
Xuanqing Liu
Cho-Jui Hsieh
GAN
11
6
0
27 Jul 2018
Limitations of the Lipschitz constant as a defense against adversarial
  examples
Limitations of the Lipschitz constant as a defense against adversarial examples
Todd P. Huster
C. Chiang
R. Chadha
AAML
6
84
0
25 Jul 2018
Motivating the Rules of the Game for Adversarial Example Research
Motivating the Rules of the Game for Adversarial Example Research
Justin Gilmer
Ryan P. Adams
Ian Goodfellow
David G. Andersen
George E. Dahl
AAML
33
226
0
18 Jul 2018
Implicit Generative Modeling of Random Noise during Training for
  Adversarial Robustness
Implicit Generative Modeling of Random Noise during Training for Adversarial Robustness
Priyadarshini Panda
Kaushik Roy
AAML
6
4
0
05 Jul 2018
Efficient ConvNets for Analog Arrays
Efficient ConvNets for Analog Arrays
M. Rasch
Tayfun Gokmen
Mattia Rigotti
W. Haensch
18
11
0
03 Jul 2018
Analysis of Invariance and Robustness via Invertibility of ReLU-Networks
Analysis of Invariance and Robustness via Invertibility of ReLU-Networks
Jens Behrmann
Sören Dittmer
Pascal Fernsel
Peter Maass
14
12
0
25 Jun 2018
Monge blunts Bayes: Hardness Results for Adversarial Training
Monge blunts Bayes: Hardness Results for Adversarial Training
Zac Cranko
A. Menon
Richard Nock
Cheng Soon Ong
Zhan Shi
Christian J. Walder
AAML
18
16
0
08 Jun 2018
The Nonlinearity Coefficient - Predicting Generalization in Deep Neural
  Networks
The Nonlinearity Coefficient - Predicting Generalization in Deep Neural Networks
George Philipp
J. Carbonell
13
14
0
01 Jun 2018
Adversarial Noise Attacks of Deep Learning Architectures -- Stability
  Analysis via Sparse Modeled Signals
Adversarial Noise Attacks of Deep Learning Architectures -- Stability Analysis via Sparse Modeled Signals
Yaniv Romano
Aviad Aberdam
Jeremias Sulam
Michael Elad
AAML
14
22
0
29 May 2018
The Singular Values of Convolutional Layers
The Singular Values of Convolutional Layers
Hanie Sedghi
Vineet Gupta
Philip M. Long
FAtt
29
200
0
26 May 2018
Laplacian Networks: Bounding Indicator Function Smoothness for Neural
  Network Robustness
Laplacian Networks: Bounding Indicator Function Smoothness for Neural Network Robustness
Carlos Lassance
Vincent Gripon
Antonio Ortega
AAML
16
16
0
24 May 2018
Adversarially Robust Training through Structured Gradient Regularization
Adversarially Robust Training through Structured Gradient Regularization
Kevin Roth
Aurélien Lucchi
Sebastian Nowozin
Thomas Hofmann
16
23
0
22 May 2018
Constructing Unrestricted Adversarial Examples with Generative Models
Constructing Unrestricted Adversarial Examples with Generative Models
Yang Song
Rui Shu
Nate Kushman
Stefano Ermon
GAN
AAML
176
302
0
21 May 2018
Detecting Adversarial Samples for Deep Neural Networks through Mutation
  Testing
Detecting Adversarial Samples for Deep Neural Networks through Mutation Testing
Jingyi Wang
Jun Sun
Peixin Zhang
Xinyu Wang
AAML
13
41
0
14 May 2018
NAIS-Net: Stable Deep Networks from Non-Autonomous Differential
  Equations
NAIS-Net: Stable Deep Networks from Non-Autonomous Differential Equations
Marco Ciccone
Marco Gallieri
Jonathan Masci
Christian Osendorfer
Faustino J. Gomez
14
56
0
19 Apr 2018
Regularisation of Neural Networks by Enforcing Lipschitz Continuity
Regularisation of Neural Networks by Enforcing Lipschitz Continuity
H. Gouk
E. Frank
Bernhard Pfahringer
M. Cree
10
466
0
12 Apr 2018
Deep Neural Networks Motivated by Partial Differential Equations
Deep Neural Networks Motivated by Partial Differential Equations
Lars Ruthotto
E. Haber
AI4CE
25
483
0
12 Apr 2018
Adversarial Training Versus Weight Decay
Adversarial Training Versus Weight Decay
A. Galloway
T. Tanay
Graham W. Taylor
AAML
16
23
0
10 Apr 2018
Defending against Adversarial Images using Basis Functions
  Transformations
Defending against Adversarial Images using Basis Functions Transformations
Uri Shaham
J. Garritano
Yutaro Yamada
Ethan Weinberger
A. Cloninger
Xiuyuan Cheng
Kelly P. Stanton
Y. Kluger
AAML
11
57
0
28 Mar 2018
Stabilizing Gradients for Deep Neural Networks via Efficient SVD
  Parameterization
Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization
Jiong Zhang
Qi Lei
Inderjit S. Dhillon
7
110
0
25 Mar 2018
Deep Convolutional Compressed Sensing for LiDAR Depth Completion
Deep Convolutional Compressed Sensing for LiDAR Depth Completion
Nathaniel Chodosh
Chaoyang Wang
Simon Lucey
3DPC
3DV
25
127
0
23 Mar 2018
Improving DNN Robustness to Adversarial Attacks using Jacobian
  Regularization
Improving DNN Robustness to Adversarial Attacks using Jacobian Regularization
Daniel Jakubovitz
Raja Giryes
AAML
11
208
0
23 Mar 2018
Deep Component Analysis via Alternating Direction Neural Networks
Deep Component Analysis via Alternating Direction Neural Networks
Calvin Murdock
Ming-Fang Chang
Simon Lucey
BDL
19
20
0
16 Mar 2018
Large Margin Deep Networks for Classification
Large Margin Deep Networks for Classification
Gamaleldin F. Elsayed
Dilip Krishnan
H. Mobahi
Kevin Regan
Samy Bengio
MQ
20
281
0
15 Mar 2018
Defending against Adversarial Attack towards Deep Neural Networks via
  Collaborative Multi-task Training
Defending against Adversarial Attack towards Deep Neural Networks via Collaborative Multi-task Training
Derui Wang
Chaoran Li
S. Wen
Surya Nepal
Yang Xiang
AAML
27
29
0
14 Mar 2018
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust
  Deep Learning
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning
Nicolas Papernot
Patrick D. McDaniel
OOD
AAML
6
502
0
13 Mar 2018
Adversarial Extreme Multi-label Classification
Adversarial Extreme Multi-label Classification
Rohit Babbar
Bernhard Schölkopf
16
16
0
05 Mar 2018
Knowledge Transfer with Jacobian Matching
Knowledge Transfer with Jacobian Matching
Suraj Srinivas
F. Fleuret
13
168
0
01 Mar 2018
Retrieval-Augmented Convolutional Neural Networks for Improved
  Robustness against Adversarial Examples
Retrieval-Augmented Convolutional Neural Networks for Improved Robustness against Adversarial Examples
Jake Zhao
Kyunghyun Cho
AAML
11
20
0
26 Feb 2018
Adversarial vulnerability for any classifier
Adversarial vulnerability for any classifier
Alhussein Fawzi
Hamza Fawzi
Omar Fawzi
AAML
16
248
0
23 Feb 2018
Deep Defense: Training DNNs with Improved Adversarial Robustness
Deep Defense: Training DNNs with Improved Adversarial Robustness
Ziang Yan
Yiwen Guo
Changshui Zhang
AAML
33
109
0
23 Feb 2018
Asynchronous Byzantine Machine Learning (the case of SGD)
Asynchronous Byzantine Machine Learning (the case of SGD)
Georgios Damaskinos
El-Mahdi El-Mhamdi
R. Guerraoui
Rhicheek Patra
Mahsa Taziki
FedML
21
42
0
22 Feb 2018
The Hidden Vulnerability of Distributed Learning in Byzantium
The Hidden Vulnerability of Distributed Learning in Byzantium
El-Mahdi El-Mhamdi
R. Guerraoui
Sébastien Rouault
AAML
FedML
13
732
0
22 Feb 2018
L2-Nonexpansive Neural Networks
L2-Nonexpansive Neural Networks
Haifeng Qian
M. Wegman
17
74
0
22 Feb 2018
i-RevNet: Deep Invertible Networks
i-RevNet: Deep Invertible Networks
J. Jacobsen
A. Smeulders
Edouard Oyallon
16
331
0
20 Feb 2018
Deceiving End-to-End Deep Learning Malware Detectors using Adversarial
  Examples
Deceiving End-to-End Deep Learning Malware Detectors using Adversarial Examples
Felix Kreuk
A. Barak
Shir Aviv-Reuven
Moran Baruch
Benny Pinkas
Joseph Keshet
AAML
8
117
0
13 Feb 2018
Previous
123...1089
Next