Creative Commons Attribution 3.0 Unported license (CC-BY 3.0)when quoting this document, please refer to the following
DOI: 10.4230/DagRep.7.8.55
URN: urn:nbn:de:0030-drops-84302
URL: https://drops.dagstuhl.de/opus/volltexte/2018/8430/
Seshia, Sanjit A. ; Zhu, Xianjin (Jerry) ; Krause, Andreas ; Jha, Susmit
Weitere Beteiligte (Hrsg. etc.): Sanjit A. Seshia and Xiaojin (Jerry) Zhu and Andreas Krause and Susmit Jha
Machine Learning and Formal Methods (Dagstuhl Seminar 17351)
| pdf-format: |
|
Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 17351 "Machine Learning and Formal Methods". The seminar brought together practitioners and reseachers in machine learning and related areas (such as robotics) with those working in formal methods and related areas (such as programming languages and control theory). The meeting highlighted the connections between the two disciplines, and created new links between the two research communities.
BibTeX - Entry
@Article{seshia_et_al:DR:2018:8430,
author = {Sanjit A. Seshia and Xianjin (Jerry) Zhu and Andreas Krause and Susmit Jha},
title = {{Machine Learning and Formal Methods (Dagstuhl Seminar 17351)}},
pages = {55--73},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2018},
volume = {7},
number = {8},
editor = {Sanjit A. Seshia and Xiaojin (Jerry) Zhu and Andreas Krause and Susmit Jha},
publisher = {Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/opus/volltexte/2018/8430},
URN = {urn:nbn:de:0030-drops-84302},
doi = {10.4230/DagRep.7.8.55},
annote = {Keywords: Formal Methods, Machine Learning}
}
| Keywords: | Formal Methods, Machine Learning | |
| Seminar: | Dagstuhl Reports, Volume 7, Issue 8 | |
| Issue date: | 2018 | |
| Date of publication: | 06.02.2018 |
