Anti-Backdoor Learning: Training Clean Models on Poisoned Data

22 October 2021

Papers citing "Anti-Backdoor Learning: Training Clean Models on Poisoned Data"

6 / 206 papers shown

Title
Sleeper Agent: Scalable Hidden Trigger Backdoors for Neural Networks Trained from Scratch Hossein Souri Liam H. Fowl Ramalingam Chellappa Micah Goldblum Tom Goldstein SILM 31 123 0 16 Jun 2021
What Doesn't Kill You Makes You Robust(er): How to Adversarially Train against Data Poisoning Jonas Geiping Liam H. Fowl Gowthami Somepalli Micah Goldblum Michael Moeller Tom Goldstein TDI AAML SILM 22 40 0 26 Feb 2021
Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training Lue Tao Lei Feng Jinfeng Yi Sheng-Jun Huang Songcan Chen AAML 28 71 0 09 Feb 2021
Privacy and Robustness in Federated Learning: Attacks and Defenses Lingjuan Lyu Han Yu Xingjun Ma Chen Chen Lichao Sun Jun Zhao Qiang Yang Philip S. Yu FedML 183 355 0 07 Dec 2020
Backdoor Learning: A Survey Yiming Li Yong Jiang Zhifeng Li Shutao Xia AAML 45 586 0 17 Jul 2020
Clean-Label Backdoor Attacks on Video Recognition Models Shihao Zhao Xingjun Ma Xiang Zheng James Bailey Jingjing Chen Yu-Gang Jiang AAML 196 274 0 06 Mar 2020