Trusted Artificial Intelligence: Challenges and Promising Solutions-Reference-Cited by-同舟云学术

Trusted Artificial Intelligence: Challenges and Promising Solutions

Published:2022-12 Issue:S1 Volume:106 Page:S9-S13
ISSN:1064-5624
Container-title:Doklady Mathematics
language:en
Short-container-title:Dokl. Math.

Author:

Turdakov D. Yu.,Avetisyan A. I.,Arkhipenko K. V.,Antsiferova A. V.,Vatolin D. S.,Volkov S. S.,Gasnikov A. V.,Devyatkin D. A.,Drobyshevsky M. D.,Kovalenko A. P.,Krivonosov M. I.,Lukashevich N. V.,Malykh V. A.,Nikolenko S. I.,Oseledets I. V.,Perminov A. I.,Sochenkov I. V.,Tikhomirov M. M.,Fedotov A. N.,Khachay M. Yu.

Publisher

Pleiades Publishing Ltd

Subject

General Mathematics

Link

https://link.springer.com/content/pdf/10.1134/S1064562422060205.pdf

Reference20 articles.

1. State Standard R 59276–2020. Artificial intelligence systems. Trust building methods. General principles.

2. State Standard R 59921–2021. Artificial intelligence systems in clinical medicine.

3. Pull request for new fuzzing targets for the TensorFlow framework. https://github.com/google/oss-fuzz/pull/7704. Accessed October 26, 2022.

4. A. Vishnyakov, A. Fedotov, D. Kuts, A. Novikov, D. Parygina, E. Kobrin, V. Logunova, P. Belecky, and S. Kurmangaleev, “Sydr: Cutting edge dynamic symbolic execution,” in 2020 Ivannikov ISPRAS Open Conference (ISPRAS) (IEEE, 2020), pp. 46–54.

5. Pull request in PyTorch. https://github.com/pytorch/pytorch/pull/79192. Accessed October 26, 2022.

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