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For a graph $G$ and a parameter $k$, we call a vertex $k$-enabling if it belongs both to a clique of size $k$ and to an independent set of size $k$, and we call it $k$-excluding otherwise. Motivated by issues that arise in secret sharing…

Data Structures and Algorithms · Computer Science 2025-09-03 Uriel Feige , Ilia Pauzner

We consider simple random walk on the incipient infinite cluster for the spread-out model of oriented percolation on $Z^d \times Z_+$. In dimensions $d>6$, we obtain bounds on exit times, transition probabilities, and the range of the…

Probability · Mathematics 2007-09-01 Martin T. Barlow , Antal A. Jarai , Takashi Kumagai , Gordon Slade

We study random walks on the giant component of the Erd\H{o}s-R\'enyi random graph ${\cal G}(n,p)$ where $p=\lambda/n$ for $\lambda>1$ fixed. The mixing time from a worst starting point was shown by Fountoulakis and Reed, and independently…

Probability · Mathematics 2016-10-21 Nathanael Berestycki , Eyal Lubetzky , Yuval Peres , Allan Sly

In the standard planar $k$-center clustering problem, one is given a set $P$ of $n$ points in the plane, and the goal is to select $k$ center points, so as to minimize the maximum distance over points in $P$ to their nearest center. Here we…

Computational Geometry · Computer Science 2021-09-29 Hongyao Huang , Georgiy Klimenko , Benjamin Raichel

We address the problem of determining a natural local neighbourhood or "cluster" associated to a given seed vertex in an undirected graph. We formulate the task in terms of absorption times of random walks from other vertices to the vertex…

Discrete Mathematics · Computer Science 2008-10-23 Pekka Orponen , Satu Elisa Schaeffer , Vanesa Avalos Gaytán

The evolution of many stochastic systems is accurately described by random walks on graphs. We here explore the close connection between local steady-state fluctuations of random walks and the global structure of the underlying graph.…

Statistical Mechanics · Physics 2022-10-25 M. Bruderer

As an indicator of the stability of spectral clustering of an undirected weighted graph into $k$ clusters, the $k$th spectral gap of the graph Laplacian is often considered. The $k$th spectral gap is characterized in this paper as an…

Numerical Analysis · Mathematics 2020-07-10 Eleonora Andreotti , Dominik Edelmann , Nicola Guglielmi , Christian Lubich

Let $G = (V,E)$ be a graph on $n$ vertices and let $m^*(G)$ denote the size of a maximum matching in $G$. We show that for any $\delta > 0$ and for any $1 \leq k \leq (1-\delta)m^*(G)$, the down-up walk on matchings of size $k$ in $G$ mixes…

Data Structures and Algorithms · Computer Science 2024-08-08 Vishesh Jain , Clayton Mizgerd

Periodic orbits in chaotic systems form clusters, whose elements traverse approximately the same points of the phase space. The distribution of cluster sizes depends on the length n of orbits and the parameter p which controls closeness of…

Chaotic Dynamics · Physics 2015-06-15 Boris Gutkin , Vladimir Al. Osipov

In this work we study the relationship between quantum random walks on graphs and Krylov/spread complexity. We show that the latter's definition naturally emerges through a canonical method of reducing a graph to a chain, on which we can…

High Energy Physics - Theory · Physics 2026-02-24 Dimitrios Patramanis , Watse Sybesma

We consider the problem of testing small set expansion for general graphs. A graph $G$ is a $(k,\phi)$-expander if every subset of volume at most $k$ has conductance at least $\phi$. Small set expansion has recently received significant…

Data Structures and Algorithms · Computer Science 2015-01-06 Angsheng Li , Pan Peng

Most convex and nonconvex clustering algorithms come with one crucial parameter: the $k$ in $k$-means. To this day, there is not one generally accepted way to accurately determine this parameter. Popular methods are simple yet theoretically…

Machine Learning · Computer Science 2021-08-04 Sibylle Hess , Wouter Duivesteijn

In a standard cluster analysis, such as k-means, in addition to clusters locations and distances between them, it's important to know if they are connected or well separated from each other. The main focus of this paper is discovering the…

Machine Learning · Statistics 2017-05-22 Evgeny Bauman , Konstantin Bauman

In the family of clustering problems, we are given a set of objects (vertices of the graph), together with some observed pairwise similarities (edges). The goal is to identify clusters of similar objects by slightly modifying the graph to…

Data Structures and Algorithms · Computer Science 2013-06-18 Anudhyan Boral , Marek Cygan , Tomasz Kociumaka , Marcin Pilipczuk

We propose a novel graph clustering method guided by additional information on the underlying structure of the clusters (or communities). The problem is formulated as the matching of a graph to a template with smaller dimension, hence…

Machine Learning · Statistics 2021-07-06 Mateus Riva , Florian Yger , Pietro Gori , Roberto M. Cesar , Isabelle Bloch

Our problem of interest is to cluster vertices of a graph by identifying underlying community structure. Among various vertex clustering approaches, spectral clustering is one of the most popular methods because it is easy to implement…

Machine Learning · Statistics 2020-09-23 Congyuan Yang , Carey E. Priebe , Youngser Park , David J. Marchette

For which values of $k$ does a uniformly chosen $3$-regular graph $G$ on $n$ vertices typically contain $ n/k$ vertex-disjoint $k$-cycles (a $k$-cycle factor)? To date, this has been answered for $k=n$ and for $k \ll \log n$; the former,…

Combinatorics · Mathematics 2014-04-21 Jeff Kahn , Eyal Lubetzky , Nicholas Wormald

We investigate the $k$-cycle shuffle on repeated cards, namely on a deck consisting of $l$ identical copies of each of $m$ card types, with total size $n=ml$. We establish asymptotic results for the total variation mixing of this shuffle,…

Probability · Mathematics 2026-03-31 Jiahe Shen

The theory of rapid mixing random walks plays a fundamental role in the study of modern randomised algorithms. Usually, the mixing time is measured with respect to the worst initial position. It is well known that the presence of…

Probability · Mathematics 2024-01-30 Alberto Espuny Díaz , Patrick Morris , Guillem Perarnau , Oriol Serra

In this paper we study variants of the widely used spectral clustering that partitions a graph into k clusters by (1) embedding the vertices of a graph into a low-dimensional space using the bottom eigenvectors of the Laplacian matrix, and…

Data Structures and Algorithms · Computer Science 2017-02-01 Richard Peng , He Sun , Luca Zanetti