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- Titel:
Adversarial Vision Challenge
- Dokumenttyp:
- Buchbeitrag
- Autor(en):
- Brendel, Wieland; Rauber, Jonas; Kurakin, Alexey; Papernot, Nicolas; Veliqi, Behar; Mohanty, Sharada P.; Laurent, Florian; Salathé, Marcel; Bethge, Matthias; Yu, Yaodong; Zhang, Hongyang; Xu, Susu; Zhang, Hongbao; Xie, Pengtao; Xing, Eric P.; Brunner, Thomas; Diehl, Frederik; Rony, Jérôme; Hafemann, Luiz Gustavo; Cheng, Shuyu; Dong, Yinpeng; Ning, Xuefei; Li, Wenshuo; Wang, Yu
- Abstract:
- This competition was meant to facilitate measurable progress towards robust machine vision models and more generally applicable adversarial attacks. It encouraged researchers to develop query-efficient adversarial attacks that can successfully operate against a wide range of defenses while just observing the final model decision to generate adversarial examples. Conversely, the competition encouraged the development of new defenses that can resist a wide range of strong decision-based attacks. I... »
- Seitenangaben Beitrag:
- 129-153
- Herausgeber:
- Escalera, Sergio; Herbrich, Ralf
- Buchtitel:
- The NeurIPS '18 Competition
- Verlag / Institution:
- Springer International Publishing
- Verlagsort:
- Cham
- Jahr:
- 2020
- Print-ISBN:
- 978-3-030-29135-8
- Serientitel:
- The Springer Series on Challenges in Machine Learning
- DOI:
- doi:10.1007/978-3-030-29135-8_5
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