scholarly journals Two-Dimensional Partial Cubes

10.37236/8934 ◽  
2020 ◽  
Vol 27 (3) ◽  
Author(s):  
Victor Chepoi ◽  
Kolja Knauer ◽  
Manon Philibert
Keyword(s):  
Cell Structure ◽  
Low Rank ◽  
Complete Graphs ◽  
Two Dimensional ◽  
Vc Dimension ◽  
Set Systems ◽  
Sample Compression ◽  
Vertex Set ◽  
Dimension 2 ◽  
Pseudoline Arrangements

We investigate the structure of two-dimensional partial cubes, i.e., of isometric subgraphs of hypercubes whose vertex set defines a set family of VC-dimension at most 2. Equivalently, those are the partial cubes which are not contractible to the 3-cube $Q_3$ (here contraction means contracting the edges corresponding to the same coordinate of the hypercube). We show that our graphs can be obtained from two types of combinatorial cells (gated cycles and gated full subdivisions of complete graphs) via amalgams. The cell structure of two-dimensional partial cubes enables us to establish a variety of results. In particular, we prove that all partial cubes of VC-dimension 2 can be extended to ample aka lopsided partial cubes of VC-dimension 2, yielding that the set families defined by such graphs satisfy the sample compression conjecture by Littlestone and Warmuth (1986) in a strong sense. The latter is a central conjecture of the area of computational machine learning, that is far from being solved even for general set systems of VC-dimension 2. Moreover, we point out relations to tope graphs of COMs of low rank and region graphs of pseudoline arrangements.

scholarly journals Shattering-Extremal Set Systems of VC Dimension at most 2

10.37236/4548 ◽  
2014 ◽  
Vol 21 (4) ◽  
Author(s):  
Tamás Mészáros ◽  
Lajos Rónyai
Keyword(s):  
Vc Dimension ◽  
Set Systems ◽  
Dimension 2 ◽  
Extremal Set Systems ◽  
Extremal Set ◽  
Open Question

We say that a set system $\mathcal{F}\subseteq 2^{[n]}$ shatters a given set $S\subseteq [n]$ if $2^S=\{F~\cap~S ~:~F~\in~\mathcal{F}\}$. The Sauer inequality states that in general, a set system $\mathcal{F}$ shatters at least $|\mathcal{F}|$ sets. Here we concentrate on the case of equality. A set system is called shattering-extremal if it shatters exactly $|\mathcal{F}|$ sets. In this paper we characterize shattering-extremal set systems of Vapnik-Chervonenkis dimension $2$ in terms of their inclusion graphs, and as a corollary we answer an open question about leaving out elements from shattering-extremal set systems in the case of families of Vapnik-Chervonenkis dimension $2$.

scholarly journals The VC Dimension of Metric Balls under Fréchet and Hausdorff Distances

2021 ◽  
Author(s):  
Anne Driemel ◽  
André Nusser ◽  
Jeff M. Phillips ◽  
Ioannis Psarros
Keyword(s):  
Density Estimation ◽  
Lower Bounds ◽  
Upper And Lower Bounds ◽  
Similarity Metrics ◽  
Vc Dimension ◽  
Set Systems ◽  
Polygonal Curves ◽  
The Individual ◽  
Curve Similarity ◽  
Metric Balls

AbstractThe Vapnik–Chervonenkis dimension provides a notion of complexity for systems of sets. If the VC dimension is small, then knowing this can drastically simplify fundamental computational tasks such as classification, range counting, and density estimation through the use of sampling bounds. We analyze set systems where the ground set X is a set of polygonal curves in $$\mathbb {R}^d$$ R d and the sets $$\mathcal {R}$$ R are metric balls defined by curve similarity metrics, such as the Fréchet distance and the Hausdorff distance, as well as their discrete counterparts. We derive upper and lower bounds on the VC dimension that imply useful sampling bounds in the setting that the number of curves is large, but the complexity of the individual curves is small. Our upper and lower bounds are either near-quadratic or near-linear in the complexity of the curves that define the ranges and they are logarithmic in the complexity of the curves that define the ground set.

scholarly journals Crystallinity fitting using cellulose crystallite models

2014 ◽  
Vol 70 (a1) ◽  
pp. C1135-C1135
Author(s):  
Patrik Ahvenainen ◽  
Ritva Serimaa
Keyword(s):  
Diffraction Pattern ◽  
Cell Structure ◽  
Unit Cell ◽  
Scattering Data ◽  
Crystalline Cellulose ◽  
Two Dimensional ◽  
Cellulose Crystallite ◽  
Cellulose Iβ ◽  
Diffraction Peaks ◽  
Unit Cell Structure

Cellulose is the most abundant biopolymer on Earth and hence it has enormous potential as a source of renewable energy. The nanoscale properties of cellulose are also import for the wood and papermaking industries. The atomic level structure of naturally occurring cellulose Iβ allomorph is well known [1] and this atomistic model is employed in this study for the cellulose unit cell structure. The cellulose crystallinity cannot be measured directly with scattering methods, but the crystallinity of the sample can be estimated by fitting models of crystalline and amorphous contributions to the sample intensity profile. The crystallinity fitting can be enhanced by improving the cellulose fitting model or the amorphous model. We focus on the cellulose crystallite model. The nanoscale level organization of crystalline cellulose in different plant materials is less well established that the unit cell structure of cellulose Iβ. Information on the texture of the sample is obtained efficiently by measuring the sample with a two-dimensional detector. The two-dimensional diffraction pattern can be used to obtain a wealth of information in one measurement, including the crystallite size, crystallite orientation and the crystallinity of the sample. The small size of cellulose crystallites in the wood cell wall limits the information obtainable from the diffraction pattern as the diffraction peaks widen and overlap. The overlapping of certain diffraction peaks can be studied at least qualitatively by computing the diffraction patterns from crystallite models of varying dimensions. Different models for cellulose crystallite have been suggested in the literature, such as the 36 chain model [2]. We investigate how the crystallinity fitting is influenced by the selected cellulose crystallite model and evaluate the suitability of different models to experimental X-ray scattering data of plant material, wood and highly crystalline cellulose.

Perfect 1-factorizations

2019 ◽  
Vol 69 (3) ◽  
pp. 479-496 ◽  
Author(s):  
Alexander Rosa
Keyword(s):  
Pairwise Disjoint ◽  
Hamiltonian Cycle ◽  
Perfect Matching ◽  
Complete Graphs ◽  
Regular Graphs ◽  
Cubic Graphs ◽  
Vertex Set ◽  
Early Survey

AbstractLetGbe a graph with vertex-setV=V(G) and edge-setE=E(G). A 1-factorofG(also calledperfect matching) is a factor ofGof degree 1, that is, a set of pairwise disjoint edges which partitionsV. A 1-factorizationofGis a partition of its edge-setEinto 1-factors. For a graphGto have a 1-factor, |V(G)| must be even, and for a graphGto admit a 1-factorization,Gmust be regular of degreer, 1 ≤r≤ |V| − 1.One can find in the literature at least two extensive surveys [69] and [89] and also a whole book [90] devoted to 1-factorizations of (mainly) complete graphs.A 1-factorization ofGis said to beperfectif the union of any two of its distinct 1-factors is a Hamiltonian cycle ofG. An early survey on perfect 1-factorizations (abbreviated as P1F) of complete graphs is [83]. In the book [90] a whole chapter (Chapter 16) is devoted to perfect 1-factorizations of complete graphs.It is the purpose of this article to present what is known to-date on P1Fs, not only of complete graphs but also of other regular graphs, primarily cubic graphs.

Extended continued fractions, recurrence relations and two-dimensional Markov processes

1989 ◽  
Vol 21 (2) ◽  
pp. 357-375 ◽  
Author(s):  
C. E. M. Pearce
Keyword(s):  
Markov Processes ◽  
Continued Fractions ◽  
Recurrence Relations ◽  
Equilibrium Distribution ◽  
Linear Recurrence ◽  
Natural State ◽  
Two Dimensional ◽  
State Spaces ◽  
General Order ◽  
Dimension 2

Connections between Markov processes and continued fractions have long been known (see, for example, Good [8]). However the usefulness of extended continued fractions in such a context appears not to have been explored. In this paper a convergence theorem is established for a class of extended continued fractions and used to provide well-behaved solutions for some general order linear recurrence relations such as arise in connection with the equilibrium distribution of state for some Markov processes whose natural state spaces are of dimension 2. Specific application is made to a multiserver version of a queueing problem studied by Neuts and Ramalhoto [13] and to a model proposed by Cohen [5] for repeated call attempts in teletraffic.

scholarly journals GENERALIZED HILBERT–KUNZ FUNCTION IN GRADED DIMENSION 2

2016 ◽  
Vol 230 ◽  
pp. 1-17 ◽  
Author(s):  
HOLGER BRENNER ◽  
ALESSIO CAMINATA
Keyword(s):  
Rational Number ◽  
Bounded Function ◽  
Closed Field ◽  
Two Dimensional ◽  
Prime Characteristic ◽  
Algebraically Closed Field ◽  
Graded Module ◽  
Dimension 2

We prove that the generalized Hilbert–Kunz function of a graded module $M$ over a two-dimensional standard graded normal $K$-domain over an algebraically closed field $K$ of prime characteristic $p$ has the form $gHK(M,q)=e_{gHK}(M)q^{2}+\unicode[STIX]{x1D6FE}(q)$, with rational generalized Hilbert–Kunz multiplicity $e_{gHK}(M)$ and a bounded function $\unicode[STIX]{x1D6FE}(q)$. Moreover, we prove that if $R$ is a $\mathbb{Z}$-algebra, the limit for $p\rightarrow +\infty$ of the generalized Hilbert–Kunz multiplicity $e_{gHK}^{R_{p}}(M_{p})$ over the fibers $R_{p}$ exists, and it is a rational number.

Magic Valuations of Finite Graphs

1970 ◽  
Vol 13 (4) ◽  
pp. 451-461 ◽  
Author(s):  
Anton Kotzig ◽  
Alexander Rosa
Keyword(s):  
Undirected Graph ◽  
Complete Graphs ◽  
Finite Graphs ◽  
Vertex Set ◽  
Multiple Edges

The purpose of this paper is to investigate for graphs the existence of certain valuations which have some "magic" property. The question about the existence of such valuations arises from the investigation of another kind of valuations which are introduced in [1] and are related to cyclic decompositions of complete graphs into isomorphic subgraphs.Throughout this paper the word graph will mean a finite undirected graph without loops or multiple edges having at least one edge. By G(m, n) we denote a graph having m vertices and n edges, by V(G) and E(G) the vertex-set and the edge-set of G, respectively. Both vertices and edges are called the elements of the graph.

A two dimensional lattice of knots by C2m-moves

2013 ◽  
Vol 155 (1) ◽  
pp. 39-46 ◽  
Author(s):  
SUMIKO HORIUCHI ◽  
YOSHIYUKI OHYAMA
Keyword(s):  
Shortest Path ◽  
Finite Sequence ◽  
Two Dimensional ◽  
Dimensional Lattice ◽  
Vassiliev Invariants ◽  
Minimum Number ◽  
Vertex Set ◽  
Lattice Graph

AbstractWe consider a local move on a knot diagram, where we denote the local move by λ. If two knots K1 and K2 are transformed into each other by a finite sequence of λ-moves, the λ-distance between K1 and K2 is the minimum number of times of λ-moves needed to transform K1 into K2. A λ-distance satisfies the axioms of distance. A two dimensional lattice of knots by λ-moves is the two dimensional lattice graph which satisfies the following: the vertex set consists of oriented knots and for any two vertices K1 and K2, the distance on the graph from K1 to K2 coincides with the λ-distance between K1 and K2, where the distance on the graph means the number of edges of the shortest path which connects the two knots. Local moves called Cn-moves are closely related to Vassiliev invariants. In this paper, we show that for any given knot K, there is a two dimensional lattice of knots by C2m-moves with the vertex K.

scholarly journals BILANGAN KROMATIK LOKASI DARI GRAF P m P n ; K m P n ; DAN K , m K n

2013 ◽  
Vol 2 (1) ◽  
pp. 14
Author(s):  
Mariza Wenni
Keyword(s):  
Natural Number ◽  
Chromatic Number ◽  
Cartesian Product ◽  
Complete Graphs ◽  
Chromatic Numbers ◽  
Color Code ◽  
Connected Graphs ◽  
Vertex Set ◽  
Distinct Color

Let G and H be two connected graphs. Let c be a vertex k-coloring of aconnected graph G and let = fCg be a partition of V (G) into the resultingcolor classes. For each v 2 V (G), the color code of v is dened to be k-vector: c1; C2; :::; Ck(v) =(d(v; C1); d(v; C2); :::; d(v; Ck)), where d(v; Ci) = minfd(v; x) j x 2 Cg, 1 i k. Ifdistinct vertices have distinct color codes with respect to , then c is called a locatingcoloring of G. The locating chromatic number of G is the smallest natural number ksuch that there are locating coloring with k colors in G. The Cartesian product of graphG and H is a graph with vertex set V (G) V (H), where two vertices (a; b) and (a)are adjacent whenever a = a0and bb02 E(H), or aa0i2 E(G) and b = b, denotedby GH. In this paper, we will study about the locating chromatic numbers of thecartesian product of two paths, the cartesian product of paths and complete graphs, andthe cartesian product of two complete graphs.

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