MixUp as Directional Adversarial Training

17 June 2019

Papers citing "MixUp as Directional Adversarial Training"

8 / 8 papers shown

Title
Over-training with Mixup May Hurt Generalization Zixuan Liu Ziqiao Wang Hongyu Guo Yongyi Mao NoLa 36 11 0 02 Mar 2023
A Survey of Mix-based Data Augmentation: Taxonomy, Methods, Applications, and Explainability Chengtai Cao Fan Zhou Yurou Dai Jianping Wang Kunpeng Zhang AAML 31 28 0 21 Dec 2022
Hierarchical MixUp Multi-label Classification with Imbalanced Interdisciplinary Research Proposals Meng Xiao Minjie Wu Ziyue Qiao Zhiyuan Ning Yi Du Yanjie Fu Yuanchun Zhou 38 2 0 28 Sep 2022
Semi-supervised Semantics-guided Adversarial Training for Trajectory Prediction Ruochen Jiao Xiangguo Liu Takami Sato Qi Alfred Chen Qi Zhu AAML 43 20 0 27 May 2022
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 43 17 0 09 Nov 2021
Towards Understanding the Data Dependency of Mixup-style Training Muthuraman Chidambaram Xiang Wang Yuzheng Hu Chenwei Wu Rong Ge UQCV 49 24 0 14 Oct 2021
Adversarially Optimized Mixup for Robust Classification Jason Bunk Srinjoy Chattopadhyay B. S. Manjunath S. Chandrasekaran AAML 30 8 0 22 Mar 2021
Addressing Neural Network Robustness with Mixup and Targeted Labeling Adversarial Training Alfred Laugros A. Caplier Matthieu Ospici AAML 24 19 0 19 Aug 2020