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A LINEAR-TIME ALGORITHM FOR GENERALIZED TRUST REGION SUBPROBLEMS

Rujun Jiang, Duan Li

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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Abstract

In this paper, we provide the first provable linear-time (in terms of the number of nonzero entries of the input) algorithm for approximately solving the generalized trust region subproblem (GTRS) of minimizing a quadratic function over a quadratic constraint under some regularity condition. Our algorithm is motivated by and extends a recent linear-time algorithm for the trust region subproblem by Hazan and Koren [Math. Program., 158 (2016), pp. 363-381]. However, due to the nonconvexity and noncompactness of the feasible region, such an extension is nontrivial. Our main contribution is to demonstrate that under some regularity condition, the optimal solution is in a compact and convex set and lower and upper bounds of the optimal value can be computed in linear time. Using these properties, we develop a linear-time algorithm for the GTRS.
Original languageEnglish
Pages (from-to)915-932
JournalSIAM Journal on Optimization
Volume30
Issue number1
Online published12 Mar 2020
DOIs
Publication statusPublished - 2020

Research Keywords

  • approximation algorithms
  • generalized trust region subproblem
  • linear-time complexity
  • semidefinite programming

Publisher's Copyright Statement

  • COPYRIGHT TERMS OF DEPOSITED FINAL PUBLISHED VERSION FILE: © 2020 Society for Industrial and Applied Mathematics.

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