The Fourth Workshop on Adversarial Learning Methods for Machine Learning and Data Mining (AdvML 2022)

被引:0
|
作者
Chen, Pin-Yu [1 ]
Hsieh, Cho-Jui [2 ]
Li, Bo [3 ]
Liu, Sijia [4 ]
机构
[1] IBM Res, San Jose, CA 95120 USA
[2] Univ Calif Los Angeles, Los Angeles, CA USA
[3] Univ Illinois, Champaign, IL USA
[4] Michigan State Univ, E Lansing, MI 48824 USA
关键词
adversarial machine learning; adversarial robustness;
D O I
10.1145/3534678.3542897
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Adversarial learning methods and their applications such as generative adversarial network, adversarial robustness, and security and privacy, have prevailed and revolutionized the research in machine learning and data mining. Their importance has not only been emphasized by the research community but also been widely recognized by the industry and the general public. Continuing the synergies in previous years, this third annual workshop aims to advance this research field. The AdvML'22 workshop consists of four tracks: (i) open-call paper submissions; (ii) invited speakers; (iii) rising star awards and presentations; and (iv) panel discussion on AdvML. The full details about the workshop can be found at https://sites.google.com/view/advml.
引用
收藏
页码:4858 / 4859
页数:2
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