Optimization and abstraction: a synergistic approach for analyzing neural network robustness-Reference-Cited by-同舟云学术

Optimization and abstraction: a synergistic approach for analyzing neural network robustness

Published:2019-06-08 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 40th ACM SIGPLAN Conference on Programming Language Design and Implementation
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Author:

Anderson Greg¹,Pailoor Shankara¹,Dillig Isil¹,Chaudhuri Swarat²

Affiliation:

1. University of Texas at Austin, USA

2. Rice University, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3314221.3314614

Reference57 articles.

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4. Mariusz Bojarski Davide Del Testa Daniel Dworakowski Bernhard Firner Beat Flepp Prasoon Goyal Lawrence D. Jackel Mathew Monfort Urs Muller Jiakai Zhang Xin Zhang Jake Zhao and Karol Zieba. 2016. End to End Learning for Self-Driving Cars. CoRR abs/1604.07316 (2016). http://arxiv.org/abs/1604.07316. Mariusz Bojarski Davide Del Testa Daniel Dworakowski Bernhard Firner Beat Flepp Prasoon Goyal Lawrence D. Jackel Mathew Monfort Urs Muller Jiakai Zhang Xin Zhang Jake Zhao and Karol Zieba. 2016. End to End Learning for Self-Driving Cars. CoRR abs/1604.07316 (2016). http://arxiv.org/abs/1604.07316.

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