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Title:Providing Meaningful Error Bounds for Solutions to Constrained Ill-Conditioned Linear Systems
Author(s):Cai, Linda
Contributor(s):Heath, Michael
Subject(s):constrained least square
ill-conditioned linear systems
regularization
Interior Point Method
Sequential Quadratic Programming
Ellipsoid
Computer Science
Abstract:In this paper we compare the performance of several methods for providing tight error bounds for linearly constrained ill-posed linear equation solutions. Specifically, we compare accuracy and computational cost of three methods: suboptimal, SQP, and interior point method. We conclude from the experiments that the suboptimal method yields smooth but somewhat looser bounds than the interior point and SQP methods, but it typically has the best running time performance, especially for larger problems. The SQP method is suitable for small to medium size problems, yielding relatively low running times and stable, tight bounds. The interior point method is in general relatively expensive and produces highly erratic bounds for linear systems based on integral equations.
Issue Date:2018
Genre:Conference Poster
Type:Image
URI:http://hdl.handle.net/2142/100869
Rights Information:Copyright 2018 Linda Cai
Date Available in IDEALS:2018-08-27


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