Regularization schemes for statistical inverse problems

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dc.authorid0000-0001-5401-0990en_US
dc.contributor.authorRastogi, Abhishake
dc.date.accessioned2024-07-12T20:49:22Z
dc.date.available2024-07-12T20:49:22Z
dc.date.issued2019en_US
dc.departmentFakülteler, İnsan ve Toplum Bilimleri Fakültesi, Matematik Bölümüen_US
dc.description.abstractWe study a statistical inverse learning problem, where we observe the noisy image of a quantity through a operator at some random design points. We consider the regularization schemes to reconstruct the estimator of the quantity for the ill-posed inverse problem. We develop a theoretical analysis for the minimizer of the regularization scheme using the ansatz of reproducing kernel Hilbert spaces. We discuss optimal rates of convergence for the proposed scheme, uniformly over classes of admissible solutions, defined through appropriate source conditions.en_US
dc.identifier.citationRastogi, A. (2019). Regularization schemes for statistical inverse problems. International Conference of Mathematical Sciences (ICMS 2019). s. 185.en_US
dc.identifier.endpage186en_US
dc.identifier.isbn978-605-2124-29-1
dc.identifier.startpage185en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12415/2163
dc.institutionauthorRastogi, Abhishake
dc.language.isoenen_US
dc.publisherMaltepe Üniversitesien_US
dc.relation.ispartofInternational Conference of Mathematical Sciences (ICMS 2019)en_US
dc.relation.publicationcategoryUluslararası Konferans Öğesi - Başka Kurum Yazarıen_US
dc.rightsCC0 1.0 Universal*
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/*
dc.snmzKY01528
dc.subjectStatistical inverse problemen_US
dc.subjectTikhonov regularizationen_US
dc.subjectReproducing kernel Hilbert spaceen_US
dc.subjectGeneral source conditionen_US
dc.subjectMinimax convergence ratesen_US
dc.titleRegularization schemes for statistical inverse problemsen_US
dc.typeArticle
dspace.entity.typePublication

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