Verifikation und Sicherheit für Neuronale Netze und Machine Learning

Author:

Mainzer Klaus

Publisher

Springer Fachmedien Wiesbaden

Reference22 articles.

1. Bayardo, Roberto J., und Robert C. Schrag. 1997. Using CSP look-back techniques to solve real world SAT instances. In Proceeding 14th National Conference on Artificial Intelligence (AAAI), 203–208.

2. Biere, Armin, Marijn Heule, Hans van Maaren, und Toby Walsh, Hrsg. 2009. Handbook of satisfiability. Amsterdam: IOS Press.

3. Bojarski, Mariusz, David Del Testa, Daniel Daworakowski, Bernhard Firner, Beat Flepp, Lawrence D. Prasoon Goyal, Mathew Monfort Jackel, Urs Muller, Jiakai Zhang, Xin Zhang, und Jake Zhao. 2016. End to end learning for self-driving cars. arXiv:1604-07316vl [cs.CV] 25 Apr 2016.

4. Bunel, Rudy, Ilker Turkasian, Philip H. S. Torr, Pushmeet Kohli, und M. Pawan Kumar. 2017. A unified view of piecewise linear neural network verification. A comparative study. arXiv:1711.00455.

5. Cheng, Chih-Hong, Georg Nührenberg, und Harald Ruess. 2017. Maximum resilience of artificial neural networks. In International Symposium on Automated Technology for Verification and Analysis, Lecture Notes in Computer Science, Bd. 10482, 251–268. Pune: Springer. ISBN 978-3-319-68166-5.

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