Almost-Orthogonal Bases for Inner Product Polynomials.

ITCS(2022)

引用 0|浏览21
暂无评分
摘要
In this paper, we consider low-degree polynomials of inner products between a collection of random vectors. We give an almost orthogonal basis for this vector space of polynomials when the random vectors are Gaussian, spherical, or Boolean. In all three cases, our basis admits an interesting combinatorial description based on the topology of the underlying graph of inner products. We also analyze the expected value of the product of two polynomials in our basis. In all three cases, we show that this expected value can be expressed in terms of collections of matchings on the underlying graph of inner products. In the Gaussian and Boolean cases, we show that this expected value is always non-negative. In the spherical case, we show that this expected value can be negative but we conjecture that if the underlying graph of inner products is planar then this expected value will always be non-negative. We hope that these polynomials will be a useful analytical tool in settings where one has a symmetric function of a collection of random or pseudorandom vectors.
更多
查看译文
关键词
inner product polynomials,almost-orthogonal
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要