Interpretability Based Neural Network Repair-Reference-Cited by-同舟云学术

Interpretability Based Neural Network Repair

Published:2024-09-11 Issue: Volume:35 Page:908-919
ISSN:
Container-title:Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis
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Author:

Chen Zuohui¹^ORCID,Zhou Jun¹^ORCID,Sun Youcheng²^ORCID,Wang Jingyi³^ORCID,Xuan Qi¹^ORCID,Yang Xiaoniu⁴^ORCID

Affiliation:

1. Zhejiang University of Technology, Hangzhou, China / Binjiang Institute of Artificial Intelligence, ZJUT, Hangzhou, China

2. University of Manchester, Manchester, United Kingdom

3. Zhejiang University, Hangzhou, China

4. Zhejiang University of Technology, Hangzhou, China / National Key Laboratory of Electromagnetic Space Security, Jiaxin, China

Funder

Key Research and Development Program of Zhejiang

National Natural Science Foundation of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3650212.3680330

Reference46 articles.

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3. Xinyun Chen, Chang Liu, Bo Li, Kimberly Lu, and Dawn Song. 2017. Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning. CoRR, abs/1712.05526 (2017), arXiv:1712.05526. arxiv:1712.05526

4. MAAT: a novel ensemble approach to addressing fairness and performance bugs for machine learning software

5. J. Deng W. Dong R. Socher L.-J. Li K. Li and L. Fei-Fei. 2009. ImageNet: A Large-Scale Hierarchical Image Database. In CVPR09.