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We propose two spectral algorithms for partitioning nodes in directed graphs respectively with a cyclic and an acyclic pattern of connection between groups of nodes. Our methods are based on the computation of extremal eigenvalues of the…

Data Structures and Algorithms · Computer Science 2018-05-09 H. Van Lierde , T. W. S. Chow , J. -C. Delvenne

A long-standing goal of social network research has been to alter the properties of network to achieve the desired outcome. In doing so, DeGroot's consensus model has served as the popular choice for modeling the information diffusion and…

Information Theory · Computer Science 2025-01-07 Saber Jafarizadeh

This paper proposes a quantum algorithm for Markov chain spectral gap estimation that is quasi-optimal (i.e., optimal up to a polylogarithmic factor) in the number of vertices for all parameters, and additionally quasi-optimal in the…

Quantum Physics · Physics 2026-01-13 Adam Connolly , Steven Herbert , Julien Sorci

A $k$-height on a graph $G=(V, E)$ is an assignment $V\to\{0, \ldots, k\}$ such that the value on ajacent vertices differs by at most $1$. We study the Markov chain on $k$-heights that in each step selects a vertex at random, and, if…

Discrete Mathematics · Computer Science 2024-10-14 Stefan Felsner , Daniel Heldt , Sandro Roch , Peter Winkler

The switching model is a Markov chain approach to sample graphs with fixed degree sequence uniformly at random. The recently invented Curveball algorithm for bipartite graphs applies several switches simultaneously (`trades'). Here, we…

Combinatorics · Mathematics 2018-07-27 Corrie Jacobien Carstens , Annabell Berger , Giovanni Strona

Large continuous-time Markov chains with exponentially small transition rates arise in modeling complex systems in physics, chemistry and biology. We propose a constructive graph-algorithmic approach to determine the sequence of critical…

Probability · Mathematics 2017-02-01 Tingyue Gan , Maria Cameron

We consider a matrix completion problem that exploits social or item similarity graphs as side information. We develop a universal, parameter-free, and computationally efficient algorithm that starts with hierarchical graph clustering and…

Machine Learning · Statistics 2022-01-06 Adel Elmahdy , Junhyung Ahn , Changho Suh , Soheil Mohajer

We investigate the mixing rate of a Markov chain where a combination of long distance edges and non-reversibility is introduced: as a first step, we focus here on the following graphs: starting from the cycle graph, we select random nodes…

Probability · Mathematics 2018-02-13 Balázs Gerencsér , Julien Hendrickx

Real-world optimization problems are generally not just black-box problems, but also involve mixed types of inputs in which discrete and continuous variables coexist. Such mixed-space optimization possesses the primary challenge of modeling…

Machine Learning · Computer Science 2022-02-09 Jaeyeon Ahn , Taehyeon Kim , Seyoung Yun

We give a new rapid mixing result for a natural random walk on the independent sets of a graph $G$. We show that when $G$ has bounded treewidth, this random walk -- known as the Glauber dynamics for the hardcore model -- mixes rapidly for…

Data Structures and Algorithms · Computer Science 2023-10-03 David Eppstein , Daniel Frishberg

A joint degree matrix (JDM) specifies the number of connections between nodes of given degrees in a graph, for all degree pairs and uniquely determines the degree sequence of the graph. We consider the space of all balanced realizations of…

Combinatorics · Mathematics 2015-07-14 Péter L. Erdős , István Miklós , Zoltán Toroczkai

The flip graph algorithm is a method for discovering new matrix multiplication schemes by following random walks on a graph. We introduce a version of the flip graph algorithm for matrix multiplication schemes that admit certain symmetries.…

Symbolic Computation · Computer Science 2025-02-10 Jakob Moosbauer , Michael Poole

We consider the irreducibility of switch-based Markov chains for the approximate uniform sampling of Hamiltonian cycles in a given undirected dense graph on $n$ vertices. As our main result, we show that every pair of Hamiltonian cycles in…

Combinatorics · Mathematics 2020-11-20 Pieter Kleer , Viresh Patel , Fabian Stroh

In this paper we raise the question of how to compress sparse graphs. By introducing the idea of redundancy, we find a way to measure the overlap of neighbors between nodes in networks. We exploit symmetry and information by making use of…

Statistical Mechanics · Physics 2015-04-01 Jie Sun , Erik M. Bollt , Daniel ben-Avraham

Given a graph $G$, a vertex switch of $v \in V(G)$ results in a new graph where neighbors of $v$ become nonneighbors and vice versa. This operation gives rise to an equivalence relation over the set of labeled digraphs on $n$ vertices. The…

Data Structures and Algorithms · Computer Science 2014-08-22 Nathan Lindzey

Time-homogeneous Markov chains are often used as disease progression models in studies of cost-effectiveness and optimal decision-making. Maximum likelihood estimation of these models can be challenging when data are collected at a time…

Methodology · Statistics 2022-09-26 Duncan Ermini Leaf

The switch chain is a well-known Markov chain for sampling directed graphs with a given degree sequence. While not ergodic in general, we show that it is ergodic for regular degree sequences. We then prove that the switch chain is rapidly…

Combinatorics · Mathematics 2011-10-17 Catherine Greenhill

Since 1997 a considerable effort has been spent on the study of the swap (switch) Markov chains on graphic degree sequences. Several results were proved on rapidly mixing Markov chains on regular simple, on regular directed, on half-regular…

Combinatorics · Mathematics 2019-11-07 Péter L. Erdős , Tamás Róbert Mezei , István Miklós

We show that the Jerrum-Sinclair Markov chain on matchings mixes in time $\widetilde{O}(\Delta^2 m)$ on any graph with $n$ vertices, $m$ edges, and maximum degree $\Delta$, for any constant edge weight $\lambda>0$. For general graphs with…

Data Structures and Algorithms · Computer Science 2025-04-04 Xiaoyu Chen , Weiming Feng , Zhe Ju , Tianshun Miao , Yitong Yin , Xinyuan Zhang

This paper considers the problem of randomized influence maximization over a Markovian graph process: given a fixed set of nodes whose connectivity graph is evolving as a Markov chain, estimate the probability distribution (over this fixed…

Social and Information Networks · Computer Science 2017-11-10 Buddhika Nettasinghe , Vikram Krishnamurthy