Enhancing Adversarial Defense by k-Winners-Take-All

25 May 2019

Papers citing "Enhancing Adversarial Defense by k-Winners-Take-All"

50 / 58 papers shown

Title
AutoAdvExBench: Benchmarking autonomous exploitation of adversarial example defenses Nicholas Carlini Javier Rando Edoardo Debenedetti Milad Nasr F. Tramèr AAML ELM 47 2 0 03 Mar 2025
AttackBench: Evaluating Gradient-based Attacks for Adversarial Examples Antonio Emanuele Cinà Jérôme Rony Maura Pintor Luca Demetrio Ambra Demontis Battista Biggio Ismail Ben Ayed Fabio Roli ELM AAML SILM 44 7 0 30 Apr 2024
Robust NAS under adversarial training: benchmark, theory, and beyond Yongtao Wu Fanghui Liu Carl-Johann Simon-Gabriel Grigorios G. Chrysos V. Cevher AAML OOD 35 3 0 19 Mar 2024
Enhance DNN Adversarial Robustness and Efficiency via Injecting Noise to Non-Essential Neurons Zhenyu Liu Garrett Gagnon Swagath Venkataramani Liu Liu AAML 30 0 0 06 Feb 2024
IRAD: Implicit Representation-driven Image Resampling against Adversarial Attacks Yue Cao Tianlin Li Xiaofeng Cao Ivor Tsang Yang Liu Qing Guo AAML 26 2 0 18 Oct 2023
Enhancing Robust Representation in Adversarial Training: Alignment and Exclusion Criteria Nuoyan Zhou Nannan Wang Decheng Liu Dawei Zhou Xinbo Gao AAML 33 2 0 05 Oct 2023
LLM Lies: Hallucinations are not Bugs, but Features as Adversarial Examples Jia-Yu Yao Kun-Peng Ning Zhen-Hui Liu Munan Ning Li Yuan HILM LRM AAML 26 169 0 02 Oct 2023
Synaptic Plasticity Models and Bio-Inspired Unsupervised Deep Learning: A Survey Gabriele Lagani Fabrizio Falchi Claudio Gennaro Giuseppe Amato AAML 43 6 0 30 Jul 2023
Revisiting and Advancing Adversarial Training Through A Simple Baseline Hong Liu AAML 26 0 0 13 Jun 2023
Feature Separation and Recalibration for Adversarial Robustness Woo Jae Kim Y. Cho Junsik Jung Sung-eui Yoon AAML 41 18 0 24 Mar 2023
Randomness in ML Defenses Helps Persistent Attackers and Hinders Evaluators Keane Lucas Matthew Jagielski Florian Tramèr Lujo Bauer Nicholas Carlini AAML 30 9 0 27 Feb 2023
Interpolation for Robust Learning: Data Augmentation on Wasserstein Geodesics Jiacheng Zhu Jielin Qiu Aritra Guha Zhuolin Yang X. Nguyen Bo-wen Li Ding Zhao OOD 34 2 0 04 Feb 2023
Sparse Coding in a Dual Memory System for Lifelong Learning F. Sarfraz Elahe Arani Bahram Zonooz CLL 18 20 0 28 Dec 2022
DISCO: Adversarial Defense with Local Implicit Functions Chih-Hui Ho Nuno Vasconcelos AAML 23 38 0 11 Dec 2022
Symmetry Defense Against CNN Adversarial Perturbation Attacks Blerta Lindqvist AAML 38 2 0 08 Oct 2022
Attacking Adversarial Defences by Smoothing the Loss Landscape Panagiotis Eustratiadis Henry Gouk Da Li Timothy M. Hospedales AAML 22 4 0 01 Aug 2022
Increasing Confidence in Adversarial Robustness Evaluations Roland S. Zimmermann Wieland Brendel Florian Tramèr Nicholas Carlini AAML 36 16 0 28 Jun 2022
On the Limitations of Stochastic Pre-processing Defenses Yue Gao Ilia Shumailov Kassem Fawaz Nicolas Papernot AAML SILM 39 30 0 19 Jun 2022
LADDER: Latent Boundary-guided Adversarial Training Xiaowei Zhou Ivor W. Tsang Jie Yin AAML 23 6 0 08 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
On the Convergence of Certified Robust Training with Interval Bound Propagation Yihan Wang Zhouxing Shi Quanquan Gu Cho-Jui Hsieh 25 9 0 16 Mar 2022
Concept Bottleneck Model with Additional Unsupervised Concepts Yoshihide Sawada Keigo Nakamura SSL 21 66 0 03 Feb 2022
Robust Binary Models by Pruning Randomly-initialized Networks Chen Liu Ziqi Zhao Sabine Süsstrunk Mathieu Salzmann TPM AAML MQ 29 4 0 03 Feb 2022
Efficient and Robust Classification for Sparse Attacks M. Beliaev Payam Delgosha Hamed Hassani Ramtin Pedarsani AAML 27 2 0 23 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
Stereoscopic Universal Perturbations across Different Architectures and Datasets Z. Berger Parth T. Agrawal Tianlin Liu Stefano Soatto A. Wong AAML 27 19 0 12 Dec 2021
Adaptive Perturbation for Adversarial Attack Zheng Yuan Jie Zhang Zhaoyan Jiang Liangliang Li Shiguang Shan AAML 27 3 0 27 Nov 2021
Denoised Internal Models: a Brain-Inspired Autoencoder against Adversarial Attacks Kaiyuan Liu Xingyu Li Yu-Rui Lai Hong Xie Hang Su Jiacheng Wang Chunxu Guo J. Guan Yi Zhou AAML 31 3 0 21 Nov 2021
Introducing the DOME Activation Functions Mohamed E. Hussein Wael AbdAlmageed 30 1 0 30 Sep 2021
Simple black-box universal adversarial attacks on medical image classification based on deep neural networks K. Koga Kazuhiro Takemoto AAML 22 11 0 11 Aug 2021
Meta Gradient Adversarial Attack Zheng Yuan Jie Zhang Yunpei Jia Chuanqi Tan Tao Xue Shiguang Shan AAML 49 78 0 09 Aug 2021
Advances in adversarial attacks and defenses in computer vision: A survey Naveed Akhtar Ajmal Mian Navid Kardan M. Shah AAML 26 235 0 01 Aug 2021
AID-Purifier: A Light Auxiliary Network for Boosting Adversarial Defense Duhun Hwang Eunjung Lee Wonjong Rhee AAML 167 14 0 14 Jul 2021
Less is More: Feature Selection for Adversarial Robustness with Compressive Counter-Adversarial Attacks Emre Ozfatura Muhammad Zaid Hameed Kerem Ozfatura Deniz Gunduz AAML 6 1 0 18 Jun 2021
Adversarial purification with Score-based generative models Jongmin Yoon Sung Ju Hwang Juho Lee DiffM 22 151 0 11 Jun 2021
Improving Robustness for Pose Estimation via Stable Heatmap Regression Yumeng Zhang Li Chen Yufeng Liu Xiaoyan Guo Wen Zheng Junhai Yong 21 4 0 08 May 2021
The art of defense: letting networks fool the attacker Jinlai Zhang Lyvjie Chen Binbin Liu Bojun Ouyang Jihong Zhu Minchi Kuang Houqing Wang Yanmei Meng AAML 3DPC 17 15 0 07 Apr 2021
Adversarial Attacks are Reversible with Natural Supervision Chengzhi Mao Mia Chiquer Hao Wang Junfeng Yang Carl Vondrick BDL AAML 15 54 0 26 Mar 2021
Spatio-Temporal Sparsification for General Robust Graph Convolution Networks Mingming Lu Ya Zhang OOD AAML 16 0 0 23 Mar 2021
Mind the box: $l_1$ -APGD for sparse adversarial attacks on image classifiers Francesco Croce Matthias Hein AAML 47 54 0 01 Mar 2021
Automated Discovery of Adaptive Attacks on Adversarial Defenses Chengyuan Yao Pavol Bielik Petar Tsankov Martin Vechev AAML 19 24 0 23 Feb 2021
CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Selection Hanshu Yan Jingfeng Zhang Gang Niu Jiashi Feng Vincent Y. F. Tan Masashi Sugiyama AAML 22 41 0 10 Feb 2021
Learnable Boundary Guided Adversarial Training Jiequan Cui Shu Liu Liwei Wang Jiaya Jia OOD AAML 24 124 0 23 Nov 2020
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 234 678 0 19 Oct 2020
Adversarial robustness via stochastic regularization of neural activation sensitivity Gil Fidel Ron Bitton Ziv Katzir A. Shabtai AAML 11 1 0 23 Sep 2020
Ramifications of Approximate Posterior Inference for Bayesian Deep Learning in Adversarial and Out-of-Distribution Settings John Mitros A. Pakrashi Brian Mac Namee UQCV 26 2 0 03 Sep 2020
Provably Robust Adversarial Examples Dimitar I. Dimitrov Gagandeep Singh Timon Gehr Martin Vechev AAML 21 11 0 23 Jul 2020
Smooth Adversarial Training Cihang Xie Mingxing Tan Boqing Gong Alan Yuille Quoc V. Le OOD 27 152 0 25 Jun 2020
RP2K: A Large-Scale Retail Product Dataset for Fine-Grained Image Classification Jingtian Peng Chang Xiao Yifan Li 14 44 0 22 Jun 2020
Learning to Generate Noise for Multi-Attack Robustness Divyam Madaan Jinwoo Shin Sung Ju Hwang NoLa AAML 25 25 0 22 Jun 2020