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Learning Polytopes with Fixed Facet Directions
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematics of Data and AI.ORCID iD: 0000-0002-0393-8286
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematics of Data and AI.ORCID iD: 0000-0002-0094-6491
2023 (English)In: SIAM Journal on Applied Algebra and Geometry, E-ISSN 2470-6566, Vol. 7, no 2, p. 440-469Article in journal (Refereed) Published
Abstract [en]

We consider the task of reconstructing polytopes with fixed facet directions from finitely many support function evaluations. We show that for a fixed simplicial normal fan, the least-squares estimate is given by a convex quadratic program. We study the geometry of the solution set and give a combinatorial characterization for the uniqueness of the reconstruction in this case. We provide an algorithm that, under mild assumptions, converges to the unknown input shape as the number of noisy support function evaluations increases. We also discuss limitations of our results if the restriction on the normal fan is removed.

Place, publisher, year, edition, pages
Society for Industrial & Applied Mathematics (SIAM) , 2023. Vol. 7, no 2, p. 440-469
Keywords [en]
approximation of polytopes, deformations, least-squares estimation, polyhedral regression, support functions
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-335722DOI: 10.1137/22M1481695ISI: 001073548600001Scopus ID: 2-s2.0-85165644378OAI: oai:DiVA.org:kth-335722DiVA, id: diva2:1795742
Funder
Swedish Research CouncilGöran Gustafsson Foundation for promotion of scientific research at Uppala University and Royal Institute of TechnologyWallenberg AI, Autonomous Systems and Software Program (WASP)
Note

QC 20231024

Available from: 2023-09-11 Created: 2023-09-11 Last updated: 2023-10-24Bibliographically approved

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Dostert, MariaJochemko, Katharina

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CiteExportLink to record
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