Rethinking Label Flipping Attack: From Sample Masking to Sample Thresholding

Xu, Qianqian; Yang, Zhiyong; Zhao, Yunrui; Cao, Xiaochun; Huang, Qingming

doi:10.1109/tpami.2022.3220849

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Rethinking Label Flipping Attack: From Sample Masking to Sample Thresholding

Cited by 4 publications

References 38 publications

DIFFender: Diffusion-Based Adversarial Defense Against Patch Attacks

DIFFender: Diffusion-Based Adversarial Defense Against Patch Attacks

Deep behavioral analysis of machine learning algorithms against data poisoning

Adversarial robustness enhancement in deep learning-based breast cancer classification: A multi-faceted approach to poisoning and Evasion attack mitigation

Contact Info

Product

Resources

About