Publisher
Springer International Publishing
Reference46 articles.
1. Anderson, G., Pailoor, S., Dillig, I., Chaudhuri, S.: Optimization and abstraction: a synergistic approach for analyzing neural network robustness. In: Proceedings of the 40th ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI2019), pp. 731–744. ACM (2019)
2. Biggio, B.: Security evaluation of support vector machines in adversarial environments. In: Ma, Y., Guo, G. (eds.) Support Vector Machines Applications, pp. 105–153. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-02300-7_4
3. Biggio, B., Nelson, B., Laskov, P.: Support vector machines under adversarial label noise. In: Proceedings of the 3rd Asian Conference on Machine Learning (ACML2011), pp. 97–112 (2011)
4. Carlini, N., Wagner, D.A.: Towards evaluating the robustness of neural networks. In: Proceedings of the 2017 IEEE Symposium on Security and Privacy (SP2017), pp. 39–57 (2017)
5. Chang, C.-C., Lin, C.-J.: LIBSVM: a library for support vector machines. ACM Trans. Intell. Syst. Technol. 2(3):27:1–27:27 (2011)
Cited by
13 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献