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Related papers: Graph Clustering using Effective Resistance

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We consider the problem of testing graph cluster structure: given access to a graph $G=(V, E)$, can we quickly determine whether the graph can be partitioned into a few clusters with good inner conductance, or is far from any such graph?…

Data Structures and Algorithms · Computer Science 2018-09-19 Ashish Chiplunkar , Michael Kapralov , Sanjeev Khanna , Aida Mousavifar , Yuval Peres

We present a nearly-linear time algorithm that produces high-quality sparsifiers of weighted graphs. Given as input a weighted graph $G=(V,E,w)$ and a parameter $\epsilon>0$, we produce a weighted subgraph $H=(V,\tilde{E},\tilde{w})$ of $G$…

Data Structures and Algorithms · Computer Science 2009-11-18 Daniel A. Spielman , Nikhil Srivastava

Effective resistances are ubiquitous in graph algorithms and network analysis. In this work, we study sublinear time algorithms to approximate the effective resistance of an adjacent pair $s$ and $t$. We consider the classical adjacency…

Data Structures and Algorithms · Computer Science 2023-07-06 Dongrun Cai , Xue Chen , Pan Peng

The graphical notion of effective resistance has found wide-ranging applications in many areas of pure mathematics, applied mathematics and control theory. By the nature of its construction, effective resistance can only be computed in…

Optimization and Control · Mathematics 2013-10-23 George Forrest Young , Luca Scardovi , Naomi Ehrich Leonard

In the graph clustering problem with a planted solution, the input is a graph on $n$ vertices partitioned into $k$ clusters, and the task is to infer the clusters from graph structure. A standard assumption is that clusters induce…

Data Structures and Algorithms · Computer Science 2025-11-24 Hendrik Fichtenberger , Michael Kapralov , Ekaterina Kochetkova , Silvio Lattanzi , Davide Mazzali , Weronika Wrzos-Kaminska

An edge-weighted graph $G=(V,E)$ is called stable if the value of a maximum-weight matching equals the value of a maximum-weight fractional matching. Stable graphs play an important role in some interesting game theory problems, such as…

Data Structures and Algorithms · Computer Science 2017-11-28 Zhuan Khye Koh , Laura Sanità

We prove a robust contraction decomposition theorem for $H$-minor-free graphs, which states that given an $H$-minor-free graph $G$ and an integer $p$, one can partition in polynomial time the vertices of $G$ into $p$ sets $Z_1,\dots,Z_p$…

Data Structures and Algorithms · Computer Science 2024-12-06 Sayan Bandyapadhyay , William Lochet , Daniel Lokshtanov , Dániel Marx , Pranabendu Misra , Daniel Neuen , Saket Saurabh , Prafullkumar Tale , Jie Xue

A directed graph $G=(V,E)$ is {\it strongly pseudo transitive} if there is a partition $\{A,E-A\}$ of $E$ so that graphs $G_1=(V,A)$ and $G_2=(V,E-A)$ are transitive, and additionally, if $ab\in A$ and $bc\in E $ implies that $ac\in E$. A…

Combinatorics · Mathematics 2018-06-06 Farhad Shahrokhi

Given a weighted graph $G=(V,E,w)$, a partition of $V$ is $\Delta$-bounded if the diameter of each cluster is bounded by $\Delta$. A distribution over $\Delta$-bounded partitions is a $\beta$-padded decomposition if every ball of radius…

Data Structures and Algorithms · Computer Science 2024-01-09 Arnold Filtser

Effective resistance, which originates from the field of circuits analysis, is an important graph distance in spectral graph theory. It has found numerous applications in various areas, such as graph data mining, spectral graph…

Numerical Analysis · Mathematics 2023-03-08 Zhiqiang Liu , Wenjian Yu

This paper introduces a scalable algorithmic framework (HyperEF) for spectral coarsening (decomposition) of large-scale hypergraphs by exploiting hyperedge effective resistances. Motivated by the latest theoretical framework for…

Machine Learning · Computer Science 2022-12-06 Ali Aghdaei , Zhuo Feng

Graph clustering aims to partition nodes into distinct clusters based on their similarity, thereby revealing relationships among nodes. Nevertheless, most existing methods do not fully utilize these edge weights. Leveraging edge weights in…

Machine Learning · Computer Science 2026-02-03 Haobing Liu , Yinuo Zhang , Tingting Wang , Ruobing Jiang , Yanwei Yu

Higher-order graph clustering aims to partition the graph using frequently occurring subgraphs. Motif conductance is one of the most promising higher-order graph clustering models due to its strong interpretability. However, existing motif…

Computational Complexity · Computer Science 2024-06-12 Longlong Lin , Tao Jia , Zeli Wang , Jin Zhao , Rong-Hua Li

This paper considers the problem of clustering a partially observed unweighted graph---i.e., one where for some node pairs we know there is an edge between them, for some others we know there is no edge, and for the remaining we do not know…

Machine Learning · Computer Science 2014-07-25 Yudong Chen , Ali Jalali , Sujay Sanghavi , Huan Xu

An uncertain graph $\mathcal{G} = (V, E, p : E \rightarrow (0,1])$ can be viewed as a probability space whose outcomes (referred to as \emph{possible worlds}) are subgraphs of $\mathcal{G}$ where any edge $e\in E$ occurs with probability…

Data Structures and Algorithms · Computer Science 2017-10-17 Matteo Ceccarello , Carlo Fantozzi , Andrea Pietracaprina , Geppino Pucci , Fabio Vandin

In a finite undirected graph $G=(V,E)$, a vertex $v \in V$ {\em dominates} itself and its neighbors in $G$. A vertex set $D \subseteq V$ is an {\em efficient dominating set} ({\em e.d.} for short) of $G$ if every $v \in V$ is dominated in…

Discrete Mathematics · Computer Science 2015-09-15 Andreas Brandstadt , Raffaele Mosca

We consider a new problem of designing a network with small $s$-$t$ effective resistance. In this problem, we are given an undirected graph $G=(V,E)$, two designated vertices $s,t \in V$, and a budget $k$. The goal is to choose a subgraph…

Data Structures and Algorithms · Computer Science 2019-04-09 Pak Hay Chan , Lap Chi Lau , Aaron Schild , Sam Chiu-wai Wong , Hong Zhou

Given a graph $G = (V,E)$ with vertex weights $w(v)$ and a desired number of parts $k$, the goal in graph partitioning problems is to partition the vertex set V into parts $V_1,\ldots,V_k$. Metrics for compactness, contiguity, and balance…

Data Structures and Algorithms · Computer Science 2021-02-10 Cyrus Hettle , Shixiang Zhu , Swati Gupta , Yao Xie

Effective resistance is an important metric that measures the similarity of two vertices in a graph. It has found applications in graph clustering, recommendation systems and network reliability, among others. In spite of the importance of…

Data Structures and Algorithms · Computer Science 2021-06-08 Pan Peng , Daniel Lopatta , Yuichi Yoshida , Gramoz Goranci

Graph clustering is a fundamental computational problem with a number of applications in algorithm design, machine learning, data mining, and analysis of social networks. Over the past decades, researchers have proposed a number of…

Data Structures and Algorithms · Computer Science 2019-04-12 He Sun , Luca Zanetti
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