English

Low rank approximation of polynomials

Combinatorics 2012-11-16 v1 Commutative Algebra

Abstract

Let knk\leq n. Each polynomial p\oR[x1,...,xn]p\in\oR[x_1,...,x_n] can be uniquely written as p=μμpμp=\sum_{\mu}\mu p_{\mu}, where μ\mu ranges over the set MM of all monomials in \oR[x1,...,xk]\oR[x_1,...,x_k] and where pμ\oR[xk+1,...,xn]p_{\mu}\in\oR[x_{k+1},...,x_n]. If pp is dd-homogeneous and ε>0\varepsilon>0, we say that pp is {\em ε\varepsilon-concentrated on the first kk variables} if μMdeg(μ)<dmaxx\oRnkx=1pμ(x)2εp2,\sum_{\mu\in M\atop\deg(\mu)<d}\max_{x\in\oR^{n-k}\atop\|x\|=1}p_{\mu}(x)^2\leq\varepsilon\|p\|^2, where p\|p\| is the Bombieri norm of pp. We show that for each d\oNd\in\oN and ε>0\varepsilon>0 there exists kd,εk_{d,\varepsilon} such that for each nn and each dd-homogeneous p\oR[x1,...,xn]p\in\oR[x_1,...,x_n] there exists kkd,εk\leq k_{d,\varepsilon} such that pp is ε\varepsilon-concentrated on the first kk variables {\em after some orthogonal transformation of \oRn\oR^n}. (So kd,εk_{d,\varepsilon} is independent of the number nn of variables.) We derive this as a consequence of a more general theorem on low rank approximation of polynomials.

Keywords

Cite

@article{arxiv.1211.3569,
  title  = {Low rank approximation of polynomials},
  author = {Alexander Schrijver},
  journal= {arXiv preprint arXiv:1211.3569},
  year   = {2012}
}
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