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1803.01442
Cited By

Stochastic Activation Pruning for Robust Adversarial Defense

Stochastic Activation Pruning for Robust Adversarial Defense

5 March 2018

Guneet Singh Dhillon

Kamyar Azizzadenesheli

Zachary Chase Lipton

Jeremy Bernstein

Anima Anandkumar

ArXiv (abs)PDF HTML

Papers citing "Stochastic Activation Pruning for Robust Adversarial Defense"

24 / 324 papers shown

Defensive Dropout for Hardening Deep Neural Networks under Adversarial
Attacks

Defensive Dropout for Hardening Deep Neural Networks under Adversarial Attacks

150

72

0

13 Sep 2018

Are adversarial examples inevitable?

Are adversarial examples inevitable?

Christoph Studer

398

291

0

06 Sep 2018

DeepHunter: Hunting Deep Neural Network Defects via Coverage-Guided
Fuzzing

DeepHunter: Hunting Deep Neural Network Defects via Coverage-Guided Fuzzing

Felix Juefei Xu

Yang Liu

172

41

0

04 Sep 2018

Security and Privacy Issues in Deep Learning

Security and Privacy Issues in Deep Learning

Jaehee Jang

308

87

0

31 Jul 2018

Rob-GAN: Generator, Discriminator, and Adversarial Attacker

Rob-GAN: Generator, Discriminator, and Adversarial Attacker

124

7

0

27 Jul 2018

Motivating the Rules of the Game for Adversarial Example Research

Motivating the Rules of the Game for Adversarial Example Research

Justin Gilmer

David G. Andersen

252

236

0

18 Jul 2018

Defend Deep Neural Networks Against Adversarial Examples via Fixed and
Dynamic Quantized Activation Functions

Defend Deep Neural Networks Against Adversarial Examples via Fixed and Dynamic Quantized Activation Functions

Adnan Siraj Rakin

197

51

0

18 Jul 2018

Monge blunts Bayes: Hardness Results for Adversarial Training

Monge blunts Bayes: Hardness Results for Adversarial Training

Christian J. Walder

164

17

0

08 Jun 2018

Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural
Networks

Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural Networks

Brendan Dolan-Gavitt

232

1,198

0

30 May 2018

Towards the first adversarially robust neural network model on MNIST

Towards the first adversarially robust neural network model on MNIST

Matthias Bethge

Wieland Brendel

338

380

0

23 May 2018

Breaking Transferability of Adversarial Samples with Randomness

Breaking Transferability of Adversarial Samples with Randomness

Murat Kantarcioglu

114

12

0

11 May 2018

An ADMM-Based Universal Framework for Adversarial Attacks on Deep Neural
Networks

An ADMM-Based Universal Framework for Adversarial Attacks on Deep Neural Networks

131

38

0

09 Apr 2018

Adversarial Defense based on Structure-to-Signal Autoencoders

Adversarial Defense based on Structure-to-Signal Autoencoders

Sebastián M. Palacio

141

34

0

21 Mar 2018

DeepGauge: Multi-Granularity Testing Criteria for Deep Learning Systems

DeepGauge: Multi-Granularity Testing Criteria for Deep Learning Systems

Felix Juefei Xu

...

Ting Su

Yang Liu

322

672

0

20 Mar 2018

Improving Transferability of Adversarial Examples with Input Diversity

Improving Transferability of Adversarial Examples with Input Diversity

Cihang Xie

432

1,301

0

19 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 TrainingIEEE Transactions on Dependable and Secure Computing (IEEE TDSC), 2018

252

35

0

14 Mar 2018

Deep Defense: Training DNNs with Improved Adversarial Robustness

Deep Defense: Training DNNs with Improved Adversarial Robustness

Changshui Zhang

334

119

0

23 Feb 2018

Predicting Adversarial Examples with High Confidence

Predicting Adversarial Examples with High Confidence

Graham W. Taylor

135

9

0

13 Feb 2018

Efficient Exploration through Bayesian Deep Q-Networks

Efficient Exploration through Bayesian Deep Q-Networks

Kamyar Azizzadenesheli

Anima Anandkumar

260

171

0

13 Feb 2018

Certified Robustness to Adversarial Examples with Differential Privacy

Certified Robustness to Adversarial Examples with Differential Privacy

Mathias Lécuyer

Vaggelis Atlidakis

Roxana Geambasu

705

985

0

09 Feb 2018

Hardening Deep Neural Networks via Adversarial Model Cascades

Hardening Deep Neural Networks via Adversarial Model Cascades

Deepak Vijaykeerthy

Ponnurangam Kumaraguru

200

9

0

02 Feb 2018

Obfuscated Gradients Give a False Sense of Security: Circumventing
Defenses to Adversarial Examples

Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples

Nicholas Carlini

2.4K

3,373

0

01 Feb 2018

Generative Adversarial Perturbations

Generative Adversarial Perturbations

Serge J. Belongie

463

385

0

06 Dec 2017

Towards Robust Neural Networks via Random Self-ensemble

Towards Robust Neural Networks via Random Self-ensemble

381

444

0

02 Dec 2017