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A Homological Theory of Functions: Nonuniform Boolean Complexity Separation and VC Dimension Bound Via Algebraic Topology, and a Homological Farkas Lemma

机译:函数的同调论:通过代数拓扑绑定非均匀布尔复杂度分离和VC维,以及同构Farkas引理

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In computational complexity, a complexity class is given by a set of problems or functions, and a basic challenge is to show separations of complexity classes A != B especially when A is known to be a subset of B. In this paper we introduce a homological theory of functions that can be used to establish complexity separations, while also providing other interesting consequences. We propose to associate a topological space S_A to each class of functions A, such that, to separate complexity classes A from a superclass B', it suffices to observe a change in "the number of holes", i.e. homology, in S_A as a subclass B of B' is added to A. In other words, if the homologies of S_A and S_{A union B} are different, then A != B'. We develop the underlying theory of functions based on homological commutative algebra and Stanley-Reisner theory, and prove a "maximal principle" for polynomial threshold functions that is used to recover Aspnes, Beigel, Furst, and Rudich's characterization of the polynomial threshold degree of symmetric functions. A surprising coincidence is demonstrated, where, roughly speaking, the maximal dimension of "holes" in S_A upper bounds the VC dimension of A, with equality for common computational cases such as the class of polynomial threshold functions or the class of linear functionals over the finite field of 2 elements, or common algebraic cases such as when the Stanley-Reisner ring of S_A is Cohen-Macaulay. As another interesting application of our theory, we prove a result that a priori has nothing to do with complexity separation: it characterizes when a vector subspace intersects the positive cone, in terms of homological conditions. By analogy to Farkas' result doing the same with linear conditions, we call our theorem the Homological Farkas Lemma.
机译:在计算复杂度中,复杂度类由一组问题或函数给出,一个基本挑战是显示复杂度类A!= B的分离,尤其是当已知A是B的子集时。在本文中,我们介绍一个可用于建立复杂性分离的功能同构理论,同时还提供其他有趣的结果。我们建议将拓扑空间S_A与函数A的每个类相关联,以便将复杂性类A与超类B'分开,足以观察到S_A中“孔数”(即同源性)的变化,即B'的子类B添加到A。换句话说,如果S_A和S_ {A union B}的同调性不同,则A!= B'。我们开发了基于同构可交换代数和Stanley-Reisner理论的基本函数论,并证明了多项阈值函数的“最大原理”,该函数用于恢复对称多项式阈值程度的Aspnes,Beigel,Furst和Rudich表征职能。证明了一个令人惊讶的巧合,粗略地讲,S_A上限中“孔”的最大尺寸限制了A的VC尺寸,对于常见的计算情况,例如多项式阈值函数类或线性函数类,它们具有相等的相等性。 2个元素的有限域,或常见的代数情况,例如当S_A的Stanley-Reisner环为Cohen-Macaulay时。作为我们理论的另一个有趣应用,我们证明了一个结果,即先验与复杂度分离无关:根据同构条件,它表征向量子空间何时与正锥相交。类似于法卡斯(Farkas)在线性条件下的结果,我们将我们的定理称为同源法卡斯引理。

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