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The capacity (or maximum flow) of an unicast network is known to be equal to the minimum s-t cut capacity due to the max-flow min-cut theorem. If the topology of a network (or link capacities) is dynamically changing or unknown, it is not…

Information Theory · Computer Science 2015-06-12 Yuki Fujii , Tadashi Wadayama

A graph is maximal knotless if it is edge maximal for the property of knotless embedding in $R^3$. We show that such a graph has at least $\frac74 |V|$ edges, and construct an infinite family of maximal knotless graphs with $|E| <…

Geometric Topology · Mathematics 2023-06-21 Lindsay Eakins , Thomas Fleming , Thomas W. Mattman

Let $G$ be a simple graph with $2n$ vertices and a perfect matching. We denote by $f(G)$ and $F(G)$ the minimum and maximum forcing number of $G$, respectively. Hetyei obtained that the maximum number of edges of graphs $G$ with a unique…

Combinatorics · Mathematics 2022-11-23 Qianqian Liu , Heping Zhang

Lettericity is a graph parameter responsible for many attractive structural properties. In particular, graphs of bounded lettericity have bounded linear clique-width and they are well-quasi-ordered by induced subgraphs. The latter property…

Combinatorics · Mathematics 2024-02-21 Bogdan Alecu , Mamadou Moustapha Kanté , Vadim Lozin , Viktor Zamaraev

An instance of the graph-constrained max-cut (GCMC) problem consists of (i) an undirected graph G and (ii) edge-weights on a complete undirected graph on the same vertex set. The objective is to find a subset of vertices satisfying some…

Data Structures and Algorithms · Computer Science 2018-10-18 Jon Lee , Viswanath Nagarajan , Xiangkun Shen

In this paper, we consider a random geometric graph (RGG)~\(G\) on~\(n\) nodes with adjacency distance~\(r_n\) just below the Hamiltonicity threshold and construct Hamiltonian cycles using additional edges called bridges. The bridges by…

Probability · Mathematics 2021-12-13 Ghurumuruhan Ganesan

Rigid graphs have only finitely many realizations. In the recent years significant progress was made in computing the number of such realizations. With this progress it was also possible for the first time to do computations on large sets…

Combinatorics · Mathematics 2025-02-10 Georg Grasegger

Gaussian mixture models are central to classical statistics, widely used in the information sciences, and have a rich mathematical structure. We examine their maximum likelihood estimates through the lens of algebraic statistics. The MLE is…

Statistics Theory · Mathematics 2019-04-19 Carlos Améndola , Mathias Drton , Bernd Sturmfels

Asymptotic properties of random regular graphs are object of extensive study in mathematics. In this note we argue, based on theory of spin glasses, that in random regular graphs the maximum cut size asymptotically equals the number of…

Disordered Systems and Neural Networks · Physics 2010-02-25 Lenka Zdeborová , Stefan Boettcher

A graph $G = (V,E)$ is globally rigid in $\mathbb{R}^d$ if for any generic placement $p : V \rightarrow \mathbb{R}^d$ of the vertices, the edge lengths $||p(u) - p(v)||, uv \in E$ uniquely determine $p$, up to congruence. In this paper we…

Combinatorics · Mathematics 2025-02-14 Dániel Garamvölgyi , Tibor Jordán

One of the earliest results in extremal graph theory, Mantel's theorem, states that the maximum number of edges in a triangle-free graph $G$ on $n$ vertices is $\lfloor n^2/4 \rfloor$. We investigate how this extremal bound is affected when…

Combinatorics · Mathematics 2025-07-01 Natalie Behague , Debsoumya Chakraborti , Xizhi Liu

In this paper, we study the maximum clique problem on hyperbolic random graphs. A hyperbolic random graph is a mathematical model for analyzing scale-free networks since it effectively explains the power-law degree distribution of…

Data Structures and Algorithms · Computer Science 2023-06-30 Eunjin Oh , Seunghyeok Oh

Designing well-connected graphs is a fundamental problem that frequently arises in various contexts across science and engineering. The weighted number of spanning trees, as a connectivity measure, emerges in numerous problems and plays a…

Data Structures and Algorithms · Computer Science 2016-04-13 Kasra Khosoussi , Gaurav S. Sukhatme , Shoudong Huang , Gamini Dissanayake

In algebraic statistics, the maximum likelihood degree of a statistical model is the number of complex critical points of its log-likelihood function. A priori knowledge of this number is useful for applying techniques of numerical…

Algebraic Geometry · Mathematics 2020-12-30 Jane Ivy Coons , Orlando Marigliano , Michael Ruddy

We consider the geometric random (GR) graph on the $d-$dimensional torus with the $L_\sigma$ distance measure ($1 \leq \sigma \leq \infty$). Our main result is an exact characterization of the probability that a particular labeled cycle…

Combinatorics · Mathematics 2010-10-01 Madhav P. Desai

This paper shows that the normalized maximum likelihood~(NML) code-length calculated in [1] is an upper bound on the NML code-length strictly calculated for the Gaussian Mixture Model. When we use this upper bound on the NML code-length, we…

Information Theory · Computer Science 2018-11-20 So Hirai , Kenji Yamanishi

While there have been many results on lower bounds for Max Cut in unweighted graphs, there are only few results for lower bounds for Max Cut in weighted graphs. In this paper, we launch an extensive study of lower bounds for Max Cut in…

Combinatorics · Mathematics 2024-08-13 Gregory Gutin , Anders Yeo

There are many methods to find a maximum (or maximal) clique in large networks. Due to the nature of combinatorics, computation becomes exponentially expensive as the number of vertices in a graph increases. Thus, there is a need for…

Social and Information Networks · Computer Science 2022-07-27 S. Y. Chan , K. Morgan , J. Ugon

We explore the rigidity of generic frameworks in 3-dimensions whose underlying graph is close to being planar. Specifically we consider apex graphs, edge-apex graphs and their variants and prove independence results in the generic…

Combinatorics · Mathematics 2024-02-28 Sean Dewar , Georg Grasegger , Eleftherios Kastis , Anthony Nixon , Brigitte Servatius

The choice of free parameters in network models is subjective, since it depends on what topological properties are being monitored. However, we show that the Maximum Likelihood (ML) principle indicates a unique, statistically rigorous…

Disordered Systems and Neural Networks · Physics 2008-08-07 Diego Garlaschelli , Maria I. Loffredo