Convexity of the image of a quadratic map via the relative entropy distance

被引:1
|
作者
Barvinok A. [1 ]
机构
[1] Department of Mathematics, University of Michigan, Ann Arbor, 48109-1043, MI
来源
Beiträge zur Algebra und Geometrie / Contributions to Algebra and Geometry | 2014年 / 55卷 / 2期
基金
美国国家科学基金会;
关键词
Gaussian measure; Approximate Carathéodory Theorem; Johnson-Lindenstrauss Lemma; Kullback-Leibler distance; Markov inequality; Positive semidefinite programming; Quadratic convexity; Relative entropy;
D O I
10.1007/s13366-013-0187-x
中图分类号
学科分类号
摘要
Let (Formula presented.) be a map defined by k positive definite quadratic forms on Rn. We prove that the relative entropy (Kullback-Leibler) distance from the convex hull of the image of ψ to the image of ψ is bounded above by an absolute constant. More precisely, we prove that for every point (Formula presented.) in the convex hull of the image of ψ satisfying (Formula presented.) there is a point (Formula presented.) in the image of (Formula presented.) satisfying (Formula presented.) and such that (Formula presented.). Similarly, we prove that for any integer m one can choose a convex combination b of at most m points from the image of ψ such that (Formula presented.). © 2013, The Managing Editors.
引用
收藏
页码:577 / 593
页数:16
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