Proving Robustness of KNN Against Adversarial Data Poisoning

Li, Yannan; Wang, Jingbo; Wang, Chao

doi:10.34727/2022/isbn.978-3-85448-053-2_6

Record link:

http://hdl.handle.net/20.500.12708/81318
https://doi.org/10.34727/2022/isbn.978-3-85448-053-2_6

Title:

Proving Robustness of KNN Against Adversarial Data Poisoning

Citation:

Li, Y., Wang, J., & Wang, C. (2022). Proving Robustness of KNN Against Adversarial Data Poisoning. In A. Griggio & N. Rungta (Eds.), Proceedings of the 22nd Conference on Formal Methods in Computer-Aided Design – FMCAD 2022 (pp. 7–16). TU Wien Academic Press. https://doi.org/10.34727/2022/isbn.978-3-85448-053-2_6

reposiTUm DOI:

10.34727/2022/isbn.978-3-85448-053-2_6

Publication Type:

Konferenzbeitrag - Full-Paper Contribution

Inproceedings - Full-Paper Contribution

Language:

English

Authors:

Li, Yannan
Wang, Jingbo
Wang, Chao

Editors:

Griggio, Alberto
Rungta, Neha

Organisational Unit: