Repairing misclassifications in neural networks using limited data-Reference-Cited by-同舟云学术

Repairing misclassifications in neural networks using limited data

Published:2022-04-25 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing
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Author:

Henriksen Patrick¹,Leofante Francesco¹,Lomuscio Alessio¹

Affiliation:

1. Imperial College London, London, United Kingdom

Funder

UK Royal Academy of Engineering

DARPA Assured Autonomy programme

UKRI Centre for Doctoral Training in Safe and Trusted Artificial Intelligence

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3477314.3507059

Reference43 articles.

1. M. Akintunde , E. Botoeva , P. Kouvaros , and A. Lomuscio . 2020. Verifying Strategic Abilities of Neural-symbolic Multi-agent Systems . In Proceedings of the 17th International Conference on Principles of Knowledge Representation and Reasoning (KR20) . IJCAI Press, 22--32. M. Akintunde, E. Botoeva, P. Kouvaros, and A. Lomuscio. 2020. Verifying Strategic Abilities of Neural-symbolic Multi-agent Systems. In Proceedings of the 17th International Conference on Principles of Knowledge Representation and Reasoning (KR20). IJCAI Press, 22--32.

2. Formal verification of neural agents in non-deterministic environments

3. S. Bak , H. Tran , K. Hobbs , and T. Johnson . 2020. Improved Geometric Path Enumeration for Verifying ReLU Neural Networks . In Proceedings of the 32nd International Conference on Computer Aided Verification (CAV20) (LNCS), Vol. 12224 . Springer, 66--96. S. Bak, H. Tran, K. Hobbs, and T. Johnson. 2020. Improved Geometric Path Enumeration for Verifying ReLU Neural Networks. In Proceedings of the 32nd International Conference on Computer Aided Verification (CAV20) (LNCS), Vol. 12224. Springer, 66--96.

4. B. Battern , P. Kouvaros , A. Lomuscio , and Y. Zheng . 2021. Efficient neural network verification via layer-based semidefinite relaxations and linear cuts . In In proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI21) . IJCAI, 2184--2190. B. Battern, P. Kouvaros, A. Lomuscio, and Y. Zheng. 2021. Efficient neural network verification via layer-based semidefinite relaxations and linear cuts. In In proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI21). IJCAI, 2184--2190.

5. E. Botoeva , P. Kouvaros , J. Kronqvist , A. Lomuscio , and R. Misener . 2020. Efficient Verification of Neural Networks via Dependency Analysis . In Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI20) . AAAI Press. E. Botoeva, P. Kouvaros, J. Kronqvist, A. Lomuscio, and R. Misener. 2020. Efficient Verification of Neural Networks via Dependency Analysis. In Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI20). AAAI Press.

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