Papers
Communities
Events
Blog
Pricing
Search
Open menu
Home
Papers
1803.01442
Cited By
Stochastic Activation Pruning for Robust Adversarial Defense
5 March 2018
Guneet Singh Dhillon
Kamyar Azizzadenesheli
Zachary Chase Lipton
Jeremy Bernstein
Jean Kossaifi
Aran Khanna
Anima Anandkumar
AAML
Re-assign community
ArXiv
PDF
HTML
Papers citing
"Stochastic Activation Pruning for Robust Adversarial Defense"
50 / 114 papers shown
Title
Two is Better than One: Efficient Ensemble Defense for Robust and Compact Models
Yoojin Jung
Byung Cheol Song
AAML
VLM
MQ
41
0
0
07 Apr 2025
Neuroplasticity in Artificial Intelligence -- An Overview and Inspirations on Drop In & Out Learning
Yupei Li
M. Milling
Björn Schuller
AI4CE
107
0
0
27 Mar 2025
Standard-Deviation-Inspired Regularization for Improving Adversarial Robustness
Olukorede Fakorede
Modeste Atsague
Jin Tian
AAML
42
0
0
31 Dec 2024
A Survey of Neural Network Robustness Assessment in Image Recognition
Jie Wang
Jun Ai
Minyan Lu
Haoran Su
Dan Yu
Yutao Zhang
Junda Zhu
Jingyu Liu
AAML
30
3
0
12 Apr 2024
Accelerated Smoothing: A Scalable Approach to Randomized Smoothing
Devansh Bhardwaj
Kshitiz Kaushik
Sarthak Gupta
AAML
37
0
0
12 Feb 2024
On The Relationship Between Universal Adversarial Attacks And Sparse Representations
Dana Weitzner
Raja Giryes
AAML
32
0
0
14 Nov 2023
Certifying LLM Safety against Adversarial Prompting
Aounon Kumar
Chirag Agarwal
Suraj Srinivas
Aaron Jiaxun Li
S. Feizi
Himabindu Lakkaraju
AAML
27
165
0
06 Sep 2023
A Simple and Effective Pruning Approach for Large Language Models
Mingjie Sun
Zhuang Liu
Anna Bair
J. Zico Kolter
64
359
0
20 Jun 2023
Beyond Empirical Risk Minimization: Local Structure Preserving Regularization for Improving Adversarial Robustness
Wei Wei
Jiahuan Zhou
Yingying Wu
AAML
15
0
0
29 Mar 2023
Provable Robustness for Streaming Models with a Sliding Window
Aounon Kumar
Vinu Sankar Sadasivan
S. Feizi
OOD
AAML
AI4TS
19
1
0
28 Mar 2023
Aux-Drop: Handling Haphazard Inputs in Online Learning Using Auxiliary Dropouts
Rohit Agarwal
D. K. Gupta
Alexander Horsch
Dilip K. Prasad
69
5
0
09 Mar 2023
On the Robustness of Randomized Ensembles to Adversarial Perturbations
Hassan Dbouk
Naresh R Shanbhag
AAML
23
7
0
02 Feb 2023
Towards Global Neural Network Abstractions with Locally-Exact Reconstruction
Edoardo Manino
I. Bessa
Lucas C. Cordeiro
21
1
0
21 Oct 2022
Boosting Adversarial Robustness From The Perspective of Effective Margin Regularization
Ziquan Liu
Antoni B. Chan
AAML
30
5
0
11 Oct 2022
Extremely Simple Activation Shaping for Out-of-Distribution Detection
Andrija Djurisic
Nebojsa Bozanic
Arjun Ashok
Rosanne Liu
OODD
172
151
0
20 Sep 2022
Two Heads are Better than One: Robust Learning Meets Multi-branch Models
Dong Huang
Qi Bu
Yuhao Qing
Haowen Pi
Sen Wang
Heming Cui
OOD
AAML
32
0
0
17 Aug 2022
DNNShield: Dynamic Randomized Model Sparsification, A Defense Against Adversarial Machine Learning
Mohammad Hossein Samavatian
Saikat Majumdar
Kristin Barber
R. Teodorescu
AAML
21
2
0
31 Jul 2022
Towards Efficient Adversarial Training on Vision Transformers
Boxi Wu
Jindong Gu
Zhifeng Li
Deng Cai
Xiaofei He
Wei Liu
ViT
AAML
46
38
0
21 Jul 2022
On the Limitations of Stochastic Pre-processing Defenses
Yue Gao
Ilia Shumailov
Kassem Fawaz
Nicolas Papernot
AAML
SILM
42
30
0
19 Jun 2022
Analysis and Extensions of Adversarial Training for Video Classification
K. A. Kinfu
René Vidal
AAML
33
13
0
16 Jun 2022
Guided Diffusion Model for Adversarial Purification
Jinyi Wang
Zhaoyang Lyu
Dahua Lin
Bo Dai
Hongfei Fu
DiffM
196
82
0
30 May 2022
Rethinking Bayesian Learning for Data Analysis: The Art of Prior and Inference in Sparsity-Aware Modeling
Lei Cheng
Feng Yin
Sergios Theodoridis
S. Chatzis
Tsung-Hui Chang
68
75
0
28 May 2022
DDDM: a Brain-Inspired Framework for Robust Classification
Xiyuan Chen
Xingyu Li
Yi Zhou
Tianming Yang
AAML
DiffM
40
7
0
01 May 2022
A Survey of Robust Adversarial Training in Pattern Recognition: Fundamental, Theory, and Methodologies
Zhuang Qian
Kaizhu Huang
Qiufeng Wang
Xu-Yao Zhang
OOD
AAML
ObjD
49
72
0
26 Mar 2022
Adversarial Defense via Image Denoising with Chaotic Encryption
Shi Hu
Eric T. Nalisnick
Max Welling
22
2
0
19 Mar 2022
Practical Evaluation of Adversarial Robustness via Adaptive Auto Attack
Ye Liu
Yaya Cheng
Lianli Gao
Xianglong Liu
Qilong Zhang
Jingkuan Song
AAML
37
57
0
10 Mar 2022
Sparsity Winning Twice: Better Robust Generalization from More Efficient Training
Tianlong Chen
Zhenyu Zhang
Pengju Wang
Santosh Balachandra
Haoyu Ma
Zehao Wang
Zhangyang Wang
OOD
AAML
98
47
0
20 Feb 2022
Smoothed Embeddings for Certified Few-Shot Learning
Mikhail Aleksandrovich Pautov
Olesya Kuznetsova
Nurislam Tursynbek
Aleksandr Petiushko
Ivan Oseledets
42
5
0
02 Feb 2022
Adversarially Robust Classification by Conditional Generative Model Inversion
Mitra Alirezaei
Tolga Tasdizen
AAML
14
0
0
12 Jan 2022
On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training
Chen Liu
Zhichao Huang
Mathieu Salzmann
Tong Zhang
Sabine Süsstrunk
AAML
23
13
0
14 Dec 2021
SoK: Anti-Facial Recognition Technology
Emily Wenger
Shawn Shan
Haitao Zheng
Ben Y. Zhao
PICV
32
13
0
08 Dec 2021
Adv-4-Adv: Thwarting Changing Adversarial Perturbations via Adversarial Domain Adaptation
Tianyue Zheng
Zhe Chen
Shuya Ding
Chao Cai
Jun Luo
AAML
35
5
0
01 Dec 2021
Medical Aegis: Robust adversarial protectors for medical images
Qingsong Yao
Zecheng He
S. Kevin Zhou
AAML
MedIm
30
2
0
22 Nov 2021
Natural Adversarial Objects
Felix Lau
Nishant Subramani
Sasha Harrison
Aerin Kim
E. Branson
Rosanne Liu
22
7
0
07 Nov 2021
Fast Gradient Non-sign Methods
Yaya Cheng
Jingkuan Song
Xiaosu Zhu
Qilong Zhang
Lianli Gao
Heng Tao Shen
AAML
24
11
0
25 Oct 2021
ADC: Adversarial attacks against object Detection that evade Context consistency checks
Mingjun Yin
Shasha Li
Chengyu Song
Ulugbek S. Kamilov
A. Roy-Chowdhury
S. Krishnamurthy
AAML
27
22
0
24 Oct 2021
Game Theory for Adversarial Attacks and Defenses
Shorya Sharma
AAML
11
3
0
08 Oct 2021
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks
Hanxun Huang
Yisen Wang
S. Erfani
Quanquan Gu
James Bailey
Xingjun Ma
AAML
TPM
46
100
0
07 Oct 2021
On the Noise Stability and Robustness of Adversarially Trained Networks on NVM Crossbars
Chun Tao
Deboleena Roy
I. Chakraborty
Kaushik Roy
AAML
32
2
0
19 Sep 2021
Simple Post-Training Robustness Using Test Time Augmentations and Random Forest
Gilad Cohen
Raja Giryes
AAML
35
4
0
16 Sep 2021
2-in-1 Accelerator: Enabling Random Precision Switch for Winning Both Adversarial Robustness and Efficiency
Yonggan Fu
Yang Katie Zhao
Qixuan Yu
Chaojian Li
Yingyan Lin
AAML
52
12
0
11 Sep 2021
Adversarial Parameter Defense by Multi-Step Risk Minimization
Zhiyuan Zhang
Ruixuan Luo
Xuancheng Ren
Qi Su
Liangyou Li
Xu Sun
AAML
25
6
0
07 Sep 2021
Meta Gradient Adversarial Attack
Zheng Yuan
Jie Zhang
Yunpei Jia
Chuanqi Tan
Tao Xue
Shiguang Shan
AAML
49
78
0
09 Aug 2021
GradDiv: Adversarial Robustness of Randomized Neural Networks via Gradient Diversity Regularization
Sungyoon Lee
Hoki Kim
Jaewook Lee
AAML
35
52
0
06 Jul 2021
Policy Smoothing for Provably Robust Reinforcement Learning
Aounon Kumar
Alexander Levine
S. Feizi
AAML
20
55
0
21 Jun 2021
Adversarial purification with Score-based generative models
Jongmin Yoon
Sung Ju Hwang
Juho Lee
DiffM
25
151
0
11 Jun 2021
Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks
Dequan Wang
An Ju
Evan Shelhamer
David Wagner
Trevor Darrell
AAML
26
26
0
18 May 2021
Sparta: Spatially Attentive and Adversarially Robust Activation
Qing Guo
Felix Juefei Xu
Changqing Zhou
Wei Feng
Yang Liu
Song Wang
AAML
33
4
0
18 May 2021
Salient Feature Extractor for Adversarial Defense on Deep Neural Networks
Jinyin Chen
Ruoxi Chen
Haibin Zheng
Zhaoyan Ming
Wenrong Jiang
Chen Cui
AAML
25
10
0
14 May 2021
Ensemble-in-One: Learning Ensemble within Random Gated Networks for Enhanced Adversarial Robustness
Yi Cai
Xuefei Ning
Huazhong Yang
Yu Wang
AAML
27
4
0
27 Mar 2021
1
2
3
Next