A linear-time algorithm for generalized trust region subproblems

被引:0
|
作者
Jiang, Rujun [1 ]
Li, Duan [2 ]
机构
[1] School of Data Science, Fudan University, Shanghai, China
[2] School of Data Science, City University of Hong Kong, Hong Kong
来源
SIAM Journal on Optimization | 2020年 / 30卷 / 01期
基金
中国国家自然科学基金;
关键词
Set theory - Optimal systems - Clustering algorithms;
D O I
暂无
中图分类号
学科分类号
摘要
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. © 2020 Society for Industrial and Applied Mathematics.
引用
收藏
页码:915 / 932
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