Verification and Repair of Neural Networks

Authors

  • Dario Guidotti University of Genoa

Keywords:

PEAI: Safety Robustness & Trustworthiness, ML: Adversarial Learning & Robustness, CSO: Applications, CSO: Satisfiability Modulo Theories, CSO: Constraint Satisfaction

Abstract

Neural Networks (NNs) are popular machine learning models which have found successful application in many different domains across computer science. However, it is hard to provide any formal guarantee on the behaviour of neural networks and therefore their reliability is still in doubt, especially concerning their deployment in safety and security-critical applications. Verification emerged as a promising solution to address some of these problems. In the following, I will present some of my recent efforts in verifying NNs.

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Published

2021-05-18

How to Cite

Guidotti, D. (2021). Verification and Repair of Neural Networks. Proceedings of the AAAI Conference on Artificial Intelligence, 35(18), 15714-15715. Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/17854

Issue

Section

The Twenty-Sixth AAAI/SIGAI Doctoral Consortium