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DOI 10.5286/raltr.2019004
Persistent URL http://purl.org/net/epubs/work/42012632
Record Status Checked
Record Id 42012632
Title Error estimates for iterative algorithms for minimizing regularized quadratic subproblems
Abstract We derive bounds for the objective errors and gradient residuals when finding approximations to the solution of common regularized quadratic optimization problems within evolving Krylov spaces. These provide upper bounds on the number of iterations required to achieve a given stated accuracy. We illustrate the quality of our bounds on given test examples.
Organisation STFC , SCI-COMP
Funding Information
Related Research Object(s): 44260851
Licence Information: Creative Commons Attribution 4.0 International (CC BY 4.0)
Language English (EN)
Type Details URI(s) Local file(s) Year
Report RAL Technical Reports RAL-TR-2019-004. STFC, 2019. RAL-TR-2019-004.pdf 2019