Mixup Inference: Better Exploiting Mixup to Defend Adversarial Attacks

25 September 2019

Tianyu Pang

Kun Xu

Jun Zhu

AAML

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Papers citing "Mixup Inference: Better Exploiting Mixup to Defend Adversarial Attacks"

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Title
AMPLIFY:Attention-based Mixup for Performance Improvement and Label Smoothing in Transformer Leixin Yang Yu Xiang 23 0 0 22 Sep 2023
Long-tailed Visual Recognition via Gaussian Clouded Logit Adjustment Mengke Li Yiu-ming Cheung Yang Lu 22 90 0 19 May 2023
Infinite Class Mixup Thomas Mensink Pascal Mettes 29 2 0 17 May 2023
Guidance Through Surrogate: Towards a Generic Diagnostic Attack Muzammal Naseer Salman Khan Fatih Porikli F. Khan AAML 20 1 0 30 Dec 2022
Dynamic Test-Time Augmentation via Differentiable Functions Shohei Enomoto Monikka Roslianna Busto Takeharu Eda OOD 35 5 0 09 Dec 2022
Deep Learning Training Procedure Augmentations Cristian Simionescu 11 1 0 25 Nov 2022
Local Model Reconstruction Attacks in Federated Learning and their Uses Ilias Driouich Chuan Xu Giovanni Neglia F. Giroire Eoin Thomas AAML FedML 29 2 0 28 Oct 2022
Multitask Learning from Augmented Auxiliary Data for Improving Speech Emotion Recognition S. Latif R. Rana Sara Khalifa Raja Jurdak Björn W. Schuller 20 21 0 12 Jul 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 36 30 0 19 Jun 2022
A Survey on Gradient Inversion: Attacks, Defenses and Future Directions Rui Zhang Song Guo Junxiao Wang Xin Xie Dacheng Tao 27 36 0 15 Jun 2022
Interpolated Joint Space Adversarial Training for Robust and Generalizable Defenses Chun Pong Lau Jiang-Long Liu Hossein Souri Wei-An Lin S. Feizi Ramalingam Chellappa AAML 29 12 0 12 Dec 2021
Evaluating Gradient Inversion Attacks and Defenses in Federated Learning Yangsibo Huang Samyak Gupta Zhao-quan Song Kai Li Sanjeev Arora FedML AAML SILM 12 269 0 30 Nov 2021
Graph Transplant: Node Saliency-Guided Graph Mixup with Local Structure Preservation Joonhyung Park Hajin Shim Eunho Yang 79 49 0 10 Nov 2021
MixACM: Mixup-Based Robustness Transfer via Distillation of Activated Channel Maps Muhammad Awais Fengwei Zhou Chuanlong Xie Jiawei Li Sung-Ho Bae Zhenguo Li AAML 29 17 0 09 Nov 2021
Impact of Attention on Adversarial Robustness of Image Classification Models Prachi Agrawal Narinder Singh Punn S. K. Sonbhadra Sonali Agarwal AAML 16 6 0 02 Sep 2021
Advances in adversarial attacks and defenses in computer vision: A survey Naveed Akhtar Ajmal Saeed Mian Navid Kardan M. Shah AAML 26 235 0 01 Aug 2021
Analysis and Applications of Class-wise Robustness in Adversarial Training Qi Tian Kun Kuang Ke Jiang Fei Wu Yisen Wang AAML 16 46 0 29 May 2021
Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks Dequan Wang An Ju Evan Shelhamer David A. Wagner Trevor Darrell AAML 23 26 0 18 May 2021
Adversarially Optimized Mixup for Robust Classification Jason Bunk Srinjoy Chattopadhyay B. S. Manjunath S. Chandrasekaran AAML 24 8 0 22 Mar 2021
Learning Defense Transformers for Counterattacking Adversarial Examples Jincheng Li Jiezhang Cao Yifan Zhang Jian Chen Mingkui Tan AAML 29 2 0 13 Mar 2021
Guided Interpolation for Adversarial Training Chen Chen Jingfeng Zhang Xilie Xu Tianlei Hu Gang Niu Gang Chen Masashi Sugiyama AAML 19 10 0 15 Feb 2021
Towards Domain-Agnostic Contrastive Learning Vikas Verma Minh-Thang Luong Kenji Kawaguchi Hieu H. Pham Quoc V. Le SSL 15 115 0 09 Nov 2020
Learning Loss for Test-Time Augmentation Ildoo Kim Younghoon Kim Sungwoong Kim OOD 18 90 0 22 Oct 2020
Combining Ensembles and Data Augmentation can Harm your Calibration Yeming Wen Ghassen Jerfel Rafael Muller Michael W. Dusenberry Jasper Snoek Balaji Lakshminarayanan Dustin Tran UQCV 32 63 0 19 Oct 2020
InstaHide: Instance-hiding Schemes for Private Distributed Learning Yangsibo Huang Zhao-quan Song K. Li Sanjeev Arora FedML PICV 6 150 0 06 Oct 2020
Understanding Catastrophic Overfitting in Single-step Adversarial Training Hoki Kim Woojin Lee Jaewook Lee AAML 9 107 0 05 Oct 2020
Dual Manifold Adversarial Robustness: Defense against Lp and non-Lp Adversarial Attacks Wei-An Lin Chun Pong Lau Alexander Levine Ramalingam Chellappa S. Feizi AAML 81 60 0 05 Sep 2020
Addressing Neural Network Robustness with Mixup and Targeted Labeling Adversarial Training Alfred Laugros A. Caplier Matthieu Ospici AAML 16 19 0 19 Aug 2020
Remix: Rebalanced Mixup Hsin-Ping Chou Shih-Chieh Chang Jia-Yu Pan Wei Wei Da-Cheng Juan 34 231 0 08 Jul 2020
Deep Architecture Enhancing Robustness to Noise, Adversarial Attacks, and Cross-corpus Setting for Speech Emotion Recognition S. Latif R. Rana Sara Khalifa Raja Jurdak Björn W. Schuller 33 28 0 18 May 2020
Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation Dmitry Molchanov Alexander Lyzhov Yuliya Molchanova Arsenii Ashukha Dmitry Vetrov TPM 17 84 0 21 Feb 2020
On Adaptive Attacks to Adversarial Example Defenses Florian Tramèr Nicholas Carlini Wieland Brendel A. Madry AAML 83 820 0 19 Feb 2020
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 284 5,835 0 08 Jul 2016