CONSTRUCTION OF MULTIVARIATE POLYNOMIAL APPROXIMATION KERNELS VIA SEMIDEFINITE PROGRAMMING

被引：2

作者：

Kirschner, Felix ^{[1
]}

De Klerk, Etienne ^{[1
]}

机构：

[1] Tilburg Univ, Sch Econ & Management, NL-5037 AB Tilburg, Netherlands

来源：

SIAM JOURNAL ON OPTIMIZATION | 2023年 / 33卷 / 02期

关键词：

polynomial kernel method; semidefinite programming; symmetry reduction; SDP-RELAXATIONS; OPTIMIZATION; SYMMETRY; BOUNDS; SUMS;

D O I：

10.1137/22M1494476

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper we construct a hierarchy of multivariate polynomial approximation kernels for uniformly continuous functions on the hypercube via semidefinite programming. We give details on the implementation of the semidefinite programs defining the kernels. Finally, we show how symmetry reduction may be performed to increase numerical tractability.

引用

页码：513 / 537

页数：25

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