Derivative-free stochastic bilevel optimization for inverse problems

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DOI:	https://doi.org/10.1007/s10589-025-00745-1
URL:	https://link.springer.com/article/10.1007/s10589-0...
Additional URL:	https://www.researchgate.net/publication/397117066...
URN:	urn:nbn:de:bsz:180-madoc-711257
Document Type:	Article
Year of publication Online:	2025
Date:	31 October 2025
The title of a journal, publication series:	Computational Optimization and Applications
Volume:	tba
Issue number:	tba
Page range:	1-54
Place of publication:	New York, NY [u.a.]
Publishing house:	Springer Science + Business Media
ISSN:	0926-6003 , 1573-2894
Publication language:	English
Institution:	School of Business Informatics and Mathematics > Probability Theory (Döring 2017-) School of Business Informatics and Mathematics > Mathematical Optimization (Staudigl 2023-)
Pre-existing license:	Creative Commons Attribution 4.0 International (CC BY 4.0)
Subject:	004 Computer science, internet
Keywords (English):	inverse problems , data-driven design , derivative-free optimization , Gaussian smoothing

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