Adversarial Robustness via Label-Smoothing

v1v2 (latest)

Adversarial Robustness via Label-Smoothing

27 June 2019

Morgane Goibert

ArXiv (abs)PDF HTML

Papers citing "Adversarial Robustness via Label-Smoothing"

9 / 9 papers shown

Title
Label Smoothing is Robustification against Model Misspecification Ryoya Yamasaki Toshiyuki Tanaka 167 0 0 15 May 2023
In and Out-of-Domain Text Adversarial Robustness via Label SmoothingAnnual Meeting of the Association for Computational Linguistics (ACL), 2022 Yahan Yang Soham Dan Dan Roth Insup Lee 256 8 0 20 Dec 2022
Adaptive Label Smoothing To Regularize Large-Scale Graph TrainingSDM (SDM), 2021 Kaixiong Zhou Ninghao Liu Fan Yang Zirui Liu Rui Chen Li Li Soo-Hyun Choi Helen Zhou AI4CE 150 23 0 30 Aug 2021
ROPUST: Improving Robustness through Fine-tuning with Photonic Processors and Synthetic Gradients Alessandro Cappelli Julien Launay Laurent Meunier Ruben Ohana Iacopo Poli AAML 143 4 0 06 Jul 2021
Self-Progressing Robust TrainingAAAI Conference on Artificial Intelligence (AAAI), 2020 Minhao Cheng Pin-Yu Chen Sijia Liu Shiyu Chang Cho-Jui Hsieh Payel Das AAML VLM 161 10 0 22 Dec 2020
Towards Understanding Label Smoothing Yi Tian Xu Yuanhong Xu Qi Qian Hao Li Rong Jin UQCV 167 47 0 20 Jun 2020
CAT: Customized Adversarial Training for Improved RobustnessInternational Joint Conference on Artificial Intelligence (IJCAI), 2020 Minhao Cheng Qi Lei Pin-Yu Chen Inderjit Dhillon Cho-Jui Hsieh OOD AAML 165 125 0 17 Feb 2020
Defending Against Adversarial Attacks by Suppressing the Largest Eigenvalue of Fisher Information Matrix Yaxin Peng Chaomin Shen Guixu Zhang Jinsong Fan AAML 131 13 0 13 Sep 2019
Wasserstein Adversarial Regularization (WAR) on label noise Kilian Fatras B. Bushan Sylvain Lobry Rémi Flamary D. Tuia Nicolas Courty 221 29 0 08 Apr 2019