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Quarterly of Applied Mathematics

Quarterly of Applied Mathematics

Online ISSN 1552-4485; Print ISSN 0033-569X

   
 
 

 

Iterated linear optimization


Authors: Pedro F. Felzenszwalb, Caroline J. Klivans and Alice Paul
Journal: Quart. Appl. Math. 79 (2021), 601-615
MSC (2020): Primary 90C25, 90C27, 15B48, 15A18
DOI: https://doi.org/10.1090/qam/1594
Published electronically: May 6, 2021
MathSciNet review: 4328140
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Abstract | References | Similar Articles | Additional Information

Abstract: We introduce a fixed point iteration process built on optimization of a linear function over a compact domain. We prove the process always converges to a fixed point and explore the set of fixed points in various convex sets. In particular, we consider elliptopes and derive an algebraic characterization of their fixed points. We show that the attractive fixed points of an elliptope are exactly its vertices. Finally, we discuss how fixed point iteration can be used for rounding the solution of a semidefinite programming relaxation.


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Additional Information

Pedro F. Felzenszwalb
Affiliation: School of Engineering, Brown University, Providence, Rhode Island 02912
MR Author ID: 820866
Email: pff@brown.edu

Caroline J. Klivans
Affiliation: Division of Applied Mathematics, Brown University, Providence, Rhode Island 02912
MR Author ID: 754274
Email: klivans@brown.edu

Alice Paul
Affiliation: Department of Biostatistics, Brown University, Providence, Rhode Island 02912
MR Author ID: 937436
Email: alice\textunderscore paul@brown.edu

Keywords: Fixed point iteration, linear optimization, semidefinite programming, elliptope
Received by editor(s): March 3, 2021
Received by editor(s) in revised form: March 29, 2021
Published electronically: May 6, 2021
Article copyright: © Copyright 2021 Brown University