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For any set system $H=(V,R), \ R \subseteq 2^V$, a subset $S \subseteq V$ is called \emph{shattered} if every $S' \subseteq S$ results from the intersection of $S$ with some set in $\R$. The \emph{VC-dimension} of $H$ is the size of a…

数据结构与算法 · 计算机科学 2024-05-14 David Coudert , Mónika Csikós , Guillaume Ducoffe , Laurent Viennot

Let $X$ be a set and ${\mathcal H}$ a collection of functions from $X$ to $\{0,1\}$. We say that ${\mathcal H}$ shatters a finite set $C \subset X$ if the restriction of ${\mathcal H}$ yields every possible function from $C$ to $\{0,1\}$.…

组合数学 · 数学 2021-08-31 D. Fitzpatrick , A. Iosevich , B. McDonald , E. Wyman

We study the VC-dimension of the set system on the vertex set of some graph which is induced by the family of its $k$-connected subgraphs. In particular, we give tight upper and lower bounds for the VC-dimension. Moreover, we show that…

离散数学 · 计算机科学 2016-02-03 Andrea Munaro

The VC-dimension is a well-studied and fundamental complexity measure of a set system (or hypergraph) that is central to many areas of machine learning. We establish several new results on the complexity of computing the VC-dimension. In…

计算复杂性 · 计算机科学 2025-10-24 Florent Foucaud , Harmender Gahlawat , Fionn Mc Inerney , Prafullkumar Tale

Let $\mathbb{F}_q^d$ be the $d$-dimensional vector space over the finite field with $q$ elements. For a subset $E\subseteq \mathbb{F}_q^d$ and a fixed nonzero $t\in \mathbb{F}_q$, let $\mathcal{H}_t(E)=\{h_y: y\in E\}$, where $h_y$ is the…

The VC-dimension of a family of sets is a measure of its combinatorial complexity used in machine learning theory, computational geometry, and even model theory. Computing the VC-dimension of the $k$-fold union of geometric set systems has…

组合数学 · 数学 2025-01-20 Pantelis E. Eleftheriou , Aris Papadopoulos , Francis Westhead

We introduce the problem Partial VC Dimension that asks, given a hypergraph $H=(X,E)$ and integers $k$ and $\ell$, whether one can select a set $C\subseteq X$ of $k$ vertices of $H$ such that the set $\{e\cap C, e\in E\}$ of distinct…

数据结构与算法 · 计算机科学 2019-05-29 Cristina Bazgan , Florent Foucaud , Florian Sikora

Following recent work on the VC-dimension of subsets of various pseudorandom graphs, we study the VC-dimension of Hamming graphs, which have proved somewhat resistant to the standard techniques in the literature. Our methods are elementary,…

组合数学 · 数学 2025-05-21 Christopher Housholder , Layna Mangiapanello , Steven Senger

For a finite set $X$ of points in the plane, a set $S$ in the plane, and a positive integer $k$, we say that a $k$-element subset $Y$ of $X$ is captured by $S$ if there is a homothetic copy $S'$ of $S$ such that $X\cap S' = Y$, i.e., $S'$…

组合数学 · 数学 2015-07-14 Maria Axenovich , Torsten Ueckerdt

We study the complexity of the Hitting Set problem in set systems (hypergraphs) that avoid certain sub-structures. In particular, we characterize the classical and parameterized complexity of the problem when the Vapnik-Chervonenkis…

数据结构与算法 · 计算机科学 2016-06-22 Karl Bringmann , László Kozma , Shay Moran , N. S. Narayanaswamy

Let $G = V, E$ be a simple connected undirected graph. A set $X \subseteq V$ is \emph{geodesically convex} if for any pair of vertices $x, y \in X$, all vertices on all shortest paths in $G$ from $x$ to $y$ are contained in $X$. A set $H…

离散数学 · 计算机科学 2026-04-20 Niranjan Nair

Given a set $X$ and a collection ${\mathcal H}$ of functions from $X$ to $\{0,1\}$, the VC-dimension measures the complexity of the hypothesis class $\mathcal{H}$ in the context of PAC learning. In recent years, this has been connected to…

经典分析与常微分方程 · 数学 2025-10-17 Alex Iosevich , Akos Magyar , Alex McDonald , Brian McDonald

Let $G=(V,E)$ be a graph. A $k$-neighborhood in $G$ is a set of vertices consisting of all the vertices at distance at most $k$ from some vertex of $G$. The hypergraph on vertex set $V$ which edge set consists of all the $k$-neighborhoods…

组合数学 · 数学 2014-12-05 Nicolas Bousquet , Stéphan Thomassé

Given a domain $X$ and a collection $\mathcal{H}$ of functions $h:X\to \{0,1\}$, the Vapnik-Chervonenkis (VC) dimension of $\mathcal{H}$ measures its complexity in an appropriate sense. In particular, the fundamental theorem of statistical…

For a vertex set $S\subseteq V(G)$ in a graph $G$, the {\em distance multiset}, $D(S)$, is the multiset of pairwise distances between vertices of $S$ in $G$. Two vertex sets are called {\em homometric} if their distance multisets are…

组合数学 · 数学 2012-03-07 Maria Axenovich , Lale Özkahya

Given a finite set $ S $ of points, we consider the following reconfiguration graph. The vertices are the plane spanning paths of $ S $ and there is an edge between two vertices if the two corresponding paths differ by two edges (one…

计算几何 · 计算机科学 2024-07-02 Valentino Boucard , Guilherme D. da Fonseca , Bastien Rivier

Two plane drawings of graphs on the same set of points are called disjoint compatible if their union is plane and they do not have an edge in common. Let $S$ be a convex point set of $2n \geq 10$ points and let $\mathcal{H}$ be a family of…

计算几何 · 计算机科学 2024-09-06 Oswin Aichholzer , Julia Obmann , Pavel Paták , Daniel Perz , Josef Tkadlec , Birgit Vogtenhuber

The Vapnik-\v{C}ervonenkis dimension is a complexity measure of set-systems, or hypergraphs. Its application to graphs is usually done by considering the sets of neighborhoods of the vertices (cf. Alon et al. (2006) and Chepoi, Estellon,…

组合数学 · 数学 2010-07-13 Tomasz Łuczak , Stéphan Thomassé

Let $G$ be a graph and $U\subset V(G)$ be a set of vertices. For each $v\in U$, let $h_v\colon U\to \{0, 1\}$ be the function defined by \[h_v(u)=\begin{cases} &1 ~\mbox{if}~u\sim v, u\in U\\&0 ~\mbox{if}~u\not\sim v, u\in U\end{cases},\]…

组合数学 · 数学 2023-03-15 Thang Pham , Steven Senger , Michael Tait , Nguyen Thu-Huyen

VC-dimension and VC-density are measures of combinatorial complexity of set systems. VC-dimension was first introduced in the context of statistical learning theory, and is tightly related to the sample complexity in PAC learning.…

逻辑 · 数学 2020-08-03 Bjarki Geir Benediktsson , Dugald Macpherson , Isolde Adler
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