Formal Methods Meet Machine Learning (F3ML)

Kim Larsen; Axel Legay; Gerrit Nolte; Maximilian Schlüter; Marielle Stoelinga; Bernhard Steffen

doi:10.1007/978-3-031-19759-8_24

Formal Methods Meet Machine Learning (F3ML)

Kim Larsen, Axel Legay, Gerrit Nolte, Maximilian Schlüter^*, Marielle Stoelinga, Bernhard Steffen

^*Kontaktforfatter

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

4 Citationer (Scopus)

Abstract

The field of machine learning focuses on computationally efficient, yet approximate algorithms. On the contrary, the field of formal methods focuses on mathematical rigor and provable correctness. Despite their superficial differences, both fields offer mutual benefit. Formal methods offer methods to verify and explain machine learning systems, aiding their adoption in safety critical domains. Machine learning offers approximate, computationally efficient approaches that let formal methods scale to larger problems. This paper gives an introduction to the track “Formal Methods Meets Machine Learning” (F3ML) and shortly presents its scientific contributions, structured into two thematic subthemes: One, concerning formal methods based approaches for the explanation and verification of machine learning systems, and one concerning the employment of machine learning approaches to scale formal methods.

Originalsprog	Engelsk
Titel	Leveraging Applications of Formal Methods, Verification and Validation. Adaptation and Learning - 11th International Symposium, ISoLA 2022, Proceedings
Redaktører	Tiziana Margaria, Bernhard Steffen
Antal sider	13
Forlag	Springer Science+Business Media
Publikationsdato	2022
Sider	393-405
ISBN (Trykt)	9783031197581
DOI	https://doi.org/10.1007/978-3-031-19759-8_24
Status	Udgivet - 2022
Begivenhed	11th International Symposium on Leveraging Applications of Formal Methods, Verification and Validation, ISoLA 2022 - Rhodes, Grækenland Varighed: 22 okt. 2022 → 30 okt. 2022

Konference

Konference	11th International Symposium on Leveraging Applications of Formal Methods, Verification and Validation, ISoLA 2022
Land/Område	Grækenland
By	Rhodes
Periode	22/10/2022 → 30/10/2022

Navn	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Vol/bind	13703 LNCS
ISSN	0302-9743

Bibliografisk note

Funding Information:
As organisers of the track, we would like to thank all authors for their contributions. We would also like to thank all reviewers for their insights and helpful comments and all participants of the track for asking interesting questions, giving constructive comments and partaking in lively discussions.

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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10.1007/978-3-031-19759-8_24

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Citationsformater

Larsen, K., Legay, A., Nolte, G., Schlüter, M., Stoelinga, M., & Steffen, B. (2022). Formal Methods Meet Machine Learning (F3ML). I T. Margaria, & B. Steffen (red.), Leveraging Applications of Formal Methods, Verification and Validation. Adaptation and Learning - 11th International Symposium, ISoLA 2022, Proceedings (s. 393-405). Springer Science+Business Media. https://doi.org/10.1007/978-3-031-19759-8_24

Larsen, Kim ; Legay, Axel ; Nolte, Gerrit et al. / Formal Methods Meet Machine Learning (F3ML). Leveraging Applications of Formal Methods, Verification and Validation. Adaptation and Learning - 11th International Symposium, ISoLA 2022, Proceedings. red. / Tiziana Margaria ; Bernhard Steffen. Springer Science+Business Media, 2022. s. 393-405 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bind 13703 LNCS).

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title = "Formal Methods Meet Machine Learning (F3ML)",

abstract = "The field of machine learning focuses on computationally efficient, yet approximate algorithms. On the contrary, the field of formal methods focuses on mathematical rigor and provable correctness. Despite their superficial differences, both fields offer mutual benefit. Formal methods offer methods to verify and explain machine learning systems, aiding their adoption in safety critical domains. Machine learning offers approximate, computationally efficient approaches that let formal methods scale to larger problems. This paper gives an introduction to the track “Formal Methods Meets Machine Learning” (F3ML) and shortly presents its scientific contributions, structured into two thematic subthemes: One, concerning formal methods based approaches for the explanation and verification of machine learning systems, and one concerning the employment of machine learning approaches to scale formal methods.",

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note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 11th International Symposium on Leveraging Applications of Formal Methods, Verification and Validation, ISoLA 2022 ; Conference date: 22-10-2022 Through 30-10-2022",

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Larsen, K, Legay, A, Nolte, G, Schlüter, M, Stoelinga, M & Steffen, B 2022, Formal Methods Meet Machine Learning (F3ML). i T Margaria & B Steffen (red), Leveraging Applications of Formal Methods, Verification and Validation. Adaptation and Learning - 11th International Symposium, ISoLA 2022, Proceedings. Springer Science+Business Media, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), bind 13703 LNCS, s. 393-405, 11th International Symposium on Leveraging Applications of Formal Methods, Verification and Validation, ISoLA 2022, Rhodes, Grækenland, 22/10/2022. https://doi.org/10.1007/978-3-031-19759-8_24

Formal Methods Meet Machine Learning (F3ML). / Larsen, Kim; Legay, Axel; Nolte, Gerrit et al.
Leveraging Applications of Formal Methods, Verification and Validation. Adaptation and Learning - 11th International Symposium, ISoLA 2022, Proceedings. red. / Tiziana Margaria; Bernhard Steffen. Springer Science+Business Media, 2022. s. 393-405 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bind 13703 LNCS).

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

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Larsen K, Legay A, Nolte G, Schlüter M, Stoelinga M, Steffen B. Formal Methods Meet Machine Learning (F3ML). I Margaria T, Steffen B, red., Leveraging Applications of Formal Methods, Verification and Validation. Adaptation and Learning - 11th International Symposium, ISoLA 2022, Proceedings. Springer Science+Business Media. 2022. s. 393-405. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bind 13703 LNCS). doi: 10.1007/978-3-031-19759-8_24

Formal Methods Meet Machine Learning (F3ML)

Abstract

Konference

Bibliografisk note

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