Markus Bachmayr, Geneviève Dusson, Christoph Ortner
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Specifically, we consider <inline-formula content-type=\"math/mathml\"> <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" alttext=\"f left-parenthesis x 1 comma ellipsis comma x Subscript upper N Baseline right-parenthesis\"> <mml:semantics> <mml:mrow> <mml:mi>f</mml:mi> <mml:mo stretchy=\"false\">(</mml:mo> <mml:msub> <mml:mi>x</mml:mi> <mml:mn>1</mml:mn> </mml:msub> <mml:mo>,</mml:mo> <mml:mo>…<!-- … --></mml:mo> <mml:mo>,</mml:mo> <mml:msub> <mml:mi>x</mml:mi> <mml:mi>N</mml:mi> </mml:msub> <mml:mo stretchy=\"false\">)</mml:mo> </mml:mrow> <mml:annotation encoding=\"application/x-tex\">f(x_1, \\dots , x_N)</mml:annotation> </mml:semantics> </mml:math> </inline-formula>, where <inline-formula content-type=\"math/mathml\"> <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" alttext=\"x Subscript i Baseline element-of double-struck upper R Superscript d\"> <mml:semantics> <mml:mrow> <mml:msub> <mml:mi>x</mml:mi> <mml:mi>i</mml:mi> </mml:msub> <mml:mo>∈<!-- ∈ --></mml:mo> <mml:msup> <mml:mrow class=\"MJX-TeXAtom-ORD\"> <mml:mi mathvariant=\"double-struck\">R</mml:mi> </mml:mrow> <mml:mi>d</mml:mi> </mml:msup> </mml:mrow> <mml:annotation encoding=\"application/x-tex\">x_i \\in \\mathbb {R}^d</mml:annotation> </mml:semantics> </mml:math> </inline-formula>, and <inline-formula content-type=\"math/mathml\"> <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" alttext=\"f\"> <mml:semantics> <mml:mi>f</mml:mi> <mml:annotation encoding=\"application/x-tex\">f</mml:annotation> </mml:semantics> </mml:math> </inline-formula> is invariant under permutations of its <inline-formula content-type=\"math/mathml\"> <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" alttext=\"upper N\"> <mml:semantics> <mml:mi>N</mml:mi> <mml:annotation encoding=\"application/x-tex\">N</mml:annotation> </mml:semantics> </mml:math> </inline-formula> arguments. We demonstrate how these symmetries can be exploited to improve the cost versus error ratio in a polynomial approximation of the function <inline-formula content-type=\"math/mathml\"> <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" alttext=\"f\"> <mml:semantics> <mml:mi>f</mml:mi> <mml:annotation encoding=\"application/x-tex\">f</mml:annotation> </mml:semantics> </mml:math> </inline-formula>, and in particular study the dependence of that ratio on <inline-formula content-type=\"math/mathml\"> <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" alttext=\"d comma upper N\"> <mml:semantics> <mml:mrow> <mml:mi>d</mml:mi> <mml:mo>,</mml:mo> <mml:mi>N</mml:mi> </mml:mrow> <mml:annotation encoding=\"application/x-tex\">d, N</mml:annotation> </mml:semantics> </mml:math> </inline-formula> and the polynomial degree. These results are then used to construct approximations and prove approximation rates for functions defined on multi-sets where <inline-formula content-type=\"math/mathml\"> <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" alttext=\"upper N\"> <mml:semantics> <mml:mi>N</mml:mi> <mml:annotation encoding=\"application/x-tex\">N</mml:annotation> </mml:semantics> </mml:math> </inline-formula> becomes a parameter of the input.","PeriodicalId":18456,"journal":{"name":"Mathematics of Computation","volume":"1 1","pages":"0"},"PeriodicalIF":2.2000,"publicationDate":"2023-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Polynomial approximation of symmetric functions\",\"authors\":\"Markus Bachmayr, Geneviève Dusson, Christoph Ortner\",\"doi\":\"10.1090/mcom/3868\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We study the polynomial approximation of symmetric multivariate functions and of multi-set functions. Specifically, we consider <inline-formula content-type=\\\"math/mathml\\\"> <mml:math xmlns:mml=\\\"http://www.w3.org/1998/Math/MathML\\\" alttext=\\\"f left-parenthesis x 1 comma ellipsis comma x Subscript upper N Baseline right-parenthesis\\\"> <mml:semantics> <mml:mrow> <mml:mi>f</mml:mi> <mml:mo stretchy=\\\"false\\\">(</mml:mo> <mml:msub> <mml:mi>x</mml:mi> <mml:mn>1</mml:mn> </mml:msub> <mml:mo>,</mml:mo> <mml:mo>…<!-- … --></mml:mo> <mml:mo>,</mml:mo> <mml:msub> <mml:mi>x</mml:mi> <mml:mi>N</mml:mi> </mml:msub> <mml:mo stretchy=\\\"false\\\">)</mml:mo> </mml:mrow> <mml:annotation encoding=\\\"application/x-tex\\\">f(x_1, \\\\dots , x_N)</mml:annotation> </mml:semantics> </mml:math> </inline-formula>, where <inline-formula content-type=\\\"math/mathml\\\"> <mml:math xmlns:mml=\\\"http://www.w3.org/1998/Math/MathML\\\" alttext=\\\"x Subscript i Baseline element-of double-struck upper R Superscript d\\\"> <mml:semantics> <mml:mrow> <mml:msub> <mml:mi>x</mml:mi> <mml:mi>i</mml:mi> </mml:msub> <mml:mo>∈<!-- ∈ --></mml:mo> <mml:msup> <mml:mrow class=\\\"MJX-TeXAtom-ORD\\\"> <mml:mi mathvariant=\\\"double-struck\\\">R</mml:mi> </mml:mrow> <mml:mi>d</mml:mi> </mml:msup> </mml:mrow> <mml:annotation encoding=\\\"application/x-tex\\\">x_i \\\\in \\\\mathbb {R}^d</mml:annotation> </mml:semantics> </mml:math> </inline-formula>, and <inline-formula content-type=\\\"math/mathml\\\"> <mml:math xmlns:mml=\\\"http://www.w3.org/1998/Math/MathML\\\" alttext=\\\"f\\\"> <mml:semantics> <mml:mi>f</mml:mi> <mml:annotation encoding=\\\"application/x-tex\\\">f</mml:annotation> </mml:semantics> </mml:math> </inline-formula> is invariant under permutations of its <inline-formula content-type=\\\"math/mathml\\\"> <mml:math xmlns:mml=\\\"http://www.w3.org/1998/Math/MathML\\\" alttext=\\\"upper N\\\"> <mml:semantics> <mml:mi>N</mml:mi> <mml:annotation encoding=\\\"application/x-tex\\\">N</mml:annotation> </mml:semantics> </mml:math> </inline-formula> arguments. We demonstrate how these symmetries can be exploited to improve the cost versus error ratio in a polynomial approximation of the function <inline-formula content-type=\\\"math/mathml\\\"> <mml:math xmlns:mml=\\\"http://www.w3.org/1998/Math/MathML\\\" alttext=\\\"f\\\"> <mml:semantics> <mml:mi>f</mml:mi> <mml:annotation encoding=\\\"application/x-tex\\\">f</mml:annotation> </mml:semantics> </mml:math> </inline-formula>, and in particular study the dependence of that ratio on <inline-formula content-type=\\\"math/mathml\\\"> <mml:math xmlns:mml=\\\"http://www.w3.org/1998/Math/MathML\\\" alttext=\\\"d comma upper N\\\"> <mml:semantics> <mml:mrow> <mml:mi>d</mml:mi> <mml:mo>,</mml:mo> <mml:mi>N</mml:mi> </mml:mrow> <mml:annotation encoding=\\\"application/x-tex\\\">d, N</mml:annotation> </mml:semantics> </mml:math> </inline-formula> and the polynomial degree. 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引用次数: 0
摘要
研究了对称多元函数和多集函数的多项式逼近问题。具体地说,我们考虑f(x 1,…,x N) f(x_1, \dots, x_N),其中x i∈R d x_i \in \mathbb {R}^d, f f在其N N个参数的置换下是不变的。我们演示了如何利用这些对称性来提高函数f的多项式近似中的成本与错误率,并特别研究了该比率对d, N, N和多项式度的依赖。然后,这些结果用于构造近似并证明在多集上定义的函数的近似率,其中N N成为输入的参数。
We study the polynomial approximation of symmetric multivariate functions and of multi-set functions. Specifically, we consider f(x1,…,xN)f(x_1, \dots , x_N), where xi∈Rdx_i \in \mathbb {R}^d, and ff is invariant under permutations of its NN arguments. We demonstrate how these symmetries can be exploited to improve the cost versus error ratio in a polynomial approximation of the function ff, and in particular study the dependence of that ratio on d,Nd, N and the polynomial degree. These results are then used to construct approximations and prove approximation rates for functions defined on multi-sets where NN becomes a parameter of the input.
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