Adversarial Attacks and Defences Competition

Autor:	Kurakin, Alexey, Goodfellow, Ian, Bengio, Samy, Dong, Yinpeng, Liao, Fangzhou, Liang, Ming, Pang, Tianyu, Zhu, Jun, Hu, Xiaolin, Xie, Cihang, Wang, Jianyu, Zhang, Zhishuai, Ren, Zhou, Yuille, Alan, Huang, Sangxia, Zhao, Yao, Zhao, Yuzhe, Han, Zhonglin, Long, Junjiajia, Berdibekov, Yerkebulan, Akiba, Takuya, Tokui, Seiya, Abe, Motoki
Rok vydání:	2018
Předmět:	Computer Science - Computer Vision and Pattern Recognition Computer Science - Cryptography and Security Computer Science - Learning Statistics - Machine Learning
Druh dokumentu:	Working Paper
Popis:	To accelerate research on adversarial examples and robustness of machine learning classifiers, Google Brain organized a NIPS 2017 competition that encouraged researchers to develop new methods to generate adversarial examples as well as to develop new ways to defend against them. In this chapter, we describe the structure and organization of the competition and the solutions developed by several of the top-placing teams. Comment: 36 pages, 10 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1804.00097 Zobrazit plný text záznamu View this record from Arxiv