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On the number of types in sparse graphs

TLDR
It is proved that for every class of graphs ℒ which is nowhere dense, and for every first order formula φ(x, y), the number of subsets of A|y| which are of the form ū for some valuation ū of x in G is bounded by O(|A||x|ε), which provides optimal bounds on the VC-density of first-order definable set systems in nowhere dense graph classes.
Abstract
We prove that for every class of graphs $\mathcal{C}$ which is nowhere dense, as defined by Nesetril and Ossona de Mendez, and for every first order formula $\phi(\bar x,\bar y)$, whenever one draws a graph $G\in \mathcal{C}$ and a subset of its nodes $A$, the number of subsets of $A^{|\bar y|}$ which are of the form $\{\bar v\in A^{|\bar y|}\, \colon\, G\models\phi(\bar u,\bar v)\}$ for some valuation $\bar u$ of $\bar x$ in $G$ is bounded by $\mathcal{O}(|A|^{|\bar x|+\epsilon})$, for every $\epsilon>0$. This provides optimal bounds on the VC-density of first-order definable set systems in nowhere dense graph classes. We also give two new proofs of upper bounds on quantities in nowhere dense classes which are relevant for their logical treatment. Firstly, we provide a new proof of the fact that nowhere dense classes are uniformly quasi-wide, implying explicit, polynomial upper bounds on the functions relating the two notions. Secondly, we give a new combinatorial proof of the result of Adler and Adler stating that every nowhere dense class of graphs is stable. In contrast to the previous proofs of the above results, our proofs are completely finitistic and constructive, and yield explicit and computable upper bounds on quantities related to uniform quasi-wideness (margins) and stability (ladder indices).

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Citations
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Proceedings ArticleDOI

Lossy Kernels for Connected Dominating Set on Sparse Graphs

TL;DR: It is shown that even though the kernelization complexity ofDominating Set and Connected Dominating Set diverges on sparse graphs this divergence is not as extreme as kernelization lower bounds suggest.
Posted Content

Progressive Algorithms for Domination and Independence

TL;DR: In this paper, a generic algorithm called progressive exploration is proposed to develop simple and efficient parameterized graph algorithms for dominating set and distance-r independent set problems, which can be used to give a linear-time fixed-parameter algorithm on any nowhere dense class.
Proceedings ArticleDOI

On the number of types in sparse graphs

TL;DR: In this article, it was shown that the VC-density of first-order definable set systems in nowhere dense graphs can be computed in polynomial time for any valuation u of x in a graph G ∈ l and a subset of its nodes A, for every e > 0.
Journal ArticleDOI

Classes of graphs with low complexity: the case of classes with bounded linear rankwidth

TL;DR: In this article, structural and model theoretic properties of classes with bounded linear rankwidth were studied from the point of view of structural graph theory and finite model theory, respectively, and it was shown that the number of unlabeled graphs of order n with linear rank-width at most r is linearly χ -bounded.
Book ChapterDOI

Linear rankwidth meets stability

TL;DR: In this paper, the structural and model theoretic properties of graph classes with bounded linear rankwidth were studied from the point of view of structural graph theory and finite model theory, respectively.
References
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Book

Graph theory

Frank Harary
Journal ArticleDOI

Learnability and the Vapnik-Chervonenkis dimension

TL;DR: This paper shows that the essential condition for distribution-free learnability is finiteness of the Vapnik-Chervonenkis dimension, a simple combinatorial parameter of the class of concepts to be learned.
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On the density of families of sets

TL;DR: This paper will answer the question in the affirmative by determining the exact upper bound of T if T is a family of subsets of some infinite set S then either there exists to each number n a set A ⊂ S with |A| = n such that |T ∩ A| = 2n or there exists some number N such that •A| c for each A⩾ N and some constant c.
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Almost optimal set covers in finite VC-dimension

TL;DR: A deterministic polynomial-time method for finding a set cover in a set system (X, ℛ) of dual VC-dimensiond such that the size of the authors' cover is at most a factor ofO(d log(dc)) from the optimal size,c.
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