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We show how to generate random derangements efficiently by two different techniques: random restricted transpositions and sequential importance sampling. The algorithm employing restricted transpositions can also be used to generate random…

Computation · Statistics 2020-08-17 J. R. G. Mendonça

For an arbitrary undirected simple graph G with m edges, we give an algorithm with running time O(m^4 |L|^2) to generate the set L of all minimal edge dominating sets of G. For bipartite graphs we obtain a better result; we show that their…

Data Structures and Algorithms · Computer Science 2012-10-24 Petr A. Golovach , Pinar Heggernes , Dieter Kratsch , Yngve Villanger

We show how to construct an overlay network of constant degree and diameter $O(\log n)$ in time $O(\log n)$ starting from an arbitrary weakly connected graph. We assume a synchronous communication network in which nodes can send messages to…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-07-28 Thorsten Götte , Kristian Hinnenthal , Christian Scheideler , Julian Werthmann

We give a quantum algorithm for a novel type of black-box problem: identifying a hidden $d$-regular base graph $G$ on $n$ vertices from oracle access to an obfuscated version of it, rather than traversing it. From $G$ we build the spired…

Quantum Physics · Physics 2026-05-13 Pawel Wocjan

Scene graphs provide a rich, structured representation of a scene by encoding the entities (objects) and their spatial relationships in a graphical format. This representation has proven useful in several tasks, such as question answering,…

Computer Vision and Pattern Recognition · Computer Science 2022-12-01 Sanjoy Kundu , Sathyanarayanan N. Aakur

We consider the problem of constructing a bipartite graph whose degrees lie in prescribed intervals. Necessary and sufficient conditions for the existence of such graphs are well-known. However, existing realization algorithms suffer from…

Data Structures and Algorithms · Computer Science 2017-08-21 Steffen Rechner

Many multivariate time series anomaly detection frameworks have been proposed and widely applied. However, most of these frameworks do not consider intrinsic relationships between variables in multivariate time series data, thus ignoring…

Machine Learning · Computer Science 2025-08-11 Falih Gozi Febrinanto , Kristen Moore , Chandra Thapa , Mujie Liu , Vidya Saikrishna , Jiangang Ma , Feng Xia

We study dynamic graph algorithms in the Massively Parallel Computation model, which was inspired by practical data processing systems. Our goal is to provide algorithms that can efficiently handle large batches of edge insertions and…

Data Structures and Algorithms · Computer Science 2021-01-12 Krzysztof Nowicki , Krzysztof Onak

We propose a novel way of generalizing the class of interval graphs, via a graph width parameter called the simultaneous interval number. This parameter is related to the simultaneous representation problem for interval graphs and defined…

Discrete Mathematics · Computer Science 2024-04-17 Jesse Beisegel , Nina Chiarelli , Ekkehard Köhler , Martin Milanič , Peter Muršič , Robert Scheffler

In this thesis, which is supervised by Dr. David Penman, we examine random interval graphs. Recall that such a graph is defined by letting $X_{1},\ldots X_{n},Y_{1},\ldots Y_{n}$ be $2n$ independent random variables, with uniform…

Combinatorics · Mathematics 2019-05-27 Vasileios Iliopoulos

Here I present the present the first major result of a novel form of network analysis - a temporal interpretation. Treating numerical edges labels as the time at which an interaction occurs between the two vertices comprising that edge…

Combinatorics · Mathematics 2007-05-23 Benjamin de Bivort

We consider the problem of finding all allowed edges in a bipartite graph $G=(V,E)$, i.e., all edges that are included in some maximum matching. We show that given any maximum matching in the graph, it is possible to perform this…

Discrete Mathematics · Computer Science 2011-07-26 Tamir Tassa

Consider an undirected graph $G = (VG, EG)$ and a set of six \emph{terminals} $T = \set{s_1, s_2, s_3, t_1, t_2, t_3} \subseteq VG$. The goal is to find a collection $\calP$ of three edge-disjoint paths $P_1$, $P_2$, and $P_3$, where $P_i$…

Combinatorics · Mathematics 2010-03-17 Maxim Babenko , Ignat Kolesnichenko , Ilya Razenshteyn

Given an undirected, edge-weighted graph G together with pairs of vertices, called pairs of terminals, the minimum multicut problem asks for a minimum-weight set of edges such that, after deleting these edges, the two terminals of each pair…

Data Structures and Algorithms · Computer Science 2016-11-24 Éric Colin de Verdière

In a graph $G$, a vertex subset $S\subseteq V(G)$ is said to be a dominating set of $G$ if every vertex not in $S$ is adjacent to a vertex in $S$. A dominating set $S$ of a graph $G$ is called a paired-dominating set if the induced subgraph…

Data Structures and Algorithms · Computer Science 2014-01-30 Ching-Chi Lin , Hai-Lun Tu

Multivariate time series forecasting is a challenging task because the data involves a mixture of long- and short-term patterns, with dynamic spatio-temporal dependencies among variables. Existing graph neural networks (GNN) typically model…

Machine Learning · Computer Science 2021-12-08 Zhuoling Li , Gaowei Zhang , Lingyu Xu , Jie Yu

We investigate the dynamic formation of regular random graphs. In our model, we pick a pair of nodes at random and connect them with a link if both of their degrees are smaller than d. Starting with a set of isolated nodes, we repeat this…

Statistical Mechanics · Physics 2011-11-16 E. Ben-Naim , P. L. Krapivsky

We consider the problem of assigning appearing times to the edges of a digraph in order to maximize the (average) temporal reachability between pairs of nodes. Motivated by the application to public transit networks, where edges cannot be…

Discrete Mathematics · Computer Science 2025-01-22 Filippo Brunelli , Pierluigi Crescenzi , Laurent Viennot

In this paper, we introduce a generalization of graphlets to heterogeneous networks called typed graphlets. Informally, typed graphlets are small typed induced subgraphs. Typed graphlets generalize graphlets to rich heterogeneous networks…

Social and Information Networks · Computer Science 2020-10-28 Ryan A. Rossi , Nesreen K. Ahmed , Aldo Carranza , David Arbour , Anup Rao , Sungchul Kim , Eunyee Koh

A graph generative model defines a distribution over graphs. One type of generative model is constructed by autoregressive neural networks, which sequentially add nodes and edges to generate a graph. However, the likelihood of a graph under…

Machine Learning · Statistics 2021-06-15 Xiaohui Chen , Xu Han , Jiajing Hu , Francisco J. R. Ruiz , Liping Liu