Hidden convexity of quadratic systems and its application to quadratic programming
Abstract
In this paper, we present sufficient conditions ensuring that the sum of the image of quadratic functions and the nonnegative orthant is convex. The hidden convexity of the trust-region problem with linear inequality constraints is established under a newly proposed assumption, which is compared with the previous one in [{\it Math. Program. 147, 171--206, 2014}]. We also provide a complete proof of the hidden convexity of a system of two quadratic functions in [{\it J. Glob. Optim. 56, 1045--1072, 2013}]. Furthermore, necessary and sufficient conditions for the S-lemma concerning systems of quadratic inequalities are investigated. Finally, we derive necessary and sufficient global optimality conditions and strong duality results for quadratic programming.
Cite
@article{arxiv.2601.13511,
title = {Hidden convexity of quadratic systems and its application to quadratic programming},
author = {Nguyen Quang Huy and Nguyen Huy Hung and Tran Van Nghi and Hoang Ngoc Tuan and Nguyen Van Tuyen},
journal= {arXiv preprint arXiv:2601.13511},
year = {2026}
}
Comments
20 pages