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Related papers: Improved Algorithms for Effective Resistance Compu…

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We study the problem of efficiently approximating the \textit{effective resistance} (ER) on undirected graphs, where ER is a widely used node proximity measure with applications in graph spectral sparsification, multi-class graph…

Social and Information Networks · Computer Science 2025-03-06 Guanyu Cui , Hanzhi Wang , Zhewei Wei

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

We provide new algorithms and conditional hardness for the problem of estimating effective resistances in $n$-node $m$-edge undirected, expander graphs. We provide an $\widetilde{O}(m\epsilon^{-1})$-time algorithm that produces with high…

Data Structures and Algorithms · Computer Science 2023-06-27 Rajat Vadiraj Dwaraknath , Ishani Karmarkar , Aaron Sidford

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

We consider the problem of dynamically maintaining (approximate) all-pairs effective resistances in separable graphs, which are those that admit an $n^{c}$-separator theorem for some $c<1$. We give a fully dynamic algorithm that maintains…

Data Structures and Algorithms · Computer Science 2018-08-09 Gramoz Goranci , Monika Henzinger , Pan Peng

The goal of graph inference is to design algorithms for learning properties of a hidden graph using queries to an oracle that returns information about the graph. Graph reconstruction, verification, and property testing are all types of…

Data Structures and Algorithms · Computer Science 2025-02-26 Huck Bennett , Mitchell Black , Amir Nayyeri , Evelyn Warton

We develop new $(1+\epsilon)$-approximation algorithms for finding the global minimum edge-cut in a directed edge-weighted graph, and for finding the global minimum vertex-cut in a directed vertex-weighted graph. Our algorithms are…

Data Structures and Algorithms · Computer Science 2025-12-17 Ron Mosenzon

We give a nearly optimal sublinear-time algorithm for approximating the size of a minimum vertex cover in a graph G. The algorithm may query the degree deg(v) of any vertex v of its choice, and for each 1 <= i <= deg(v), it may ask for the…

Data Structures and Algorithms · Computer Science 2011-10-06 Krzysztof Onak , Dana Ron , Michal Rosen , Ronitt Rubinfeld

We study the complexity of approximating the vertex expansion of graphs $G = (V,E)$, defined as \[ \Phi^V := \min_{S \subset V} n \cdot \frac{|N(S)|}{|S| |V \backslash S|}. \] We give a simple polynomial-time algorithm for finding a subset…

Computational Complexity · Computer Science 2013-11-12 Anand Louis , Prasad Raghavendra , Santosh Vempala

The girth of a graph, i.e. the length of its shortest cycle, is a fundamental graph parameter. Unfortunately all known algorithms for computing, even approximately, the girth and girth-related structures in directed weighted $m$-edge and…

Data Structures and Algorithms · Computer Science 2018-08-14 Jakub Pachocki , Liam Roditty , Aaron Sidford , Roei Tov , Virginia Vassilevska Williams

Effective resistance (ER) is an attractive way to interrogate the structure of graphs. It is an alternative to computing the eigenvectors of the graph Laplacian. One attractive application of ER is to point clouds, i.e. graphs whose…

Machine Learning · Computer Science 2023-06-28 Robi Bhattacharjee , Alexander Cloninger , Yoav Freund , Andreas Oslandsbotn

Graph Crossing Number is a fundamental problem with various applications. In this problem, the goal is to draw an input graph $G$ in the plane so as to minimize the number of crossings between the images of its edges. Despite extensive…

Data Structures and Algorithms · Computer Science 2021-01-12 Julia Chuzhoy , Sepideh Mahabadi , Zihan Tan

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

We present a general framework of designing efficient dynamic approximate algorithms for optimization on undirected graphs. In particular, we develop a technique that, given any problem that admits a certain notion of vertex sparsifiers,…

Data Structures and Algorithms · Computer Science 2020-05-06 Li Chen , Gramoz Goranci , Monika Henzinger , Richard Peng , Thatchaphol Saranurak

Expander graphs are known to be robust to edge deletions in the following sense: for any online sequence of edge deletions $e_1, e_2, \ldots, e_k$ to an $m$-edge graph $G$ that is initially a $\phi$-expander, the algorithm can grow a set $P…

Data Structures and Algorithms · Computer Science 2025-04-02 Simon Meierhans , Maximilian Probst Gutenberg , Thatchaphol Saranurak

We propose an efficient $\epsilon$-differentially private algorithm, that given a simple {\em weighted} $n$-vertex, $m$-edge graph $G$ with a \emph{maximum unweighted} degree $\Delta(G) \leq n-1$, outputs a synthetic graph which…

Data Structures and Algorithms · Computer Science 2023-10-02 Jingcheng Liu , Jalaj Upadhyay , Zongrui Zou

We develop a new algorithmic technique that allows to transfer some constant time approximation algorithms for general graphs into random order streaming algorithms. We illustrate our technique by proving that in random order streams with…

Data Structures and Algorithms · Computer Science 2017-11-15 Pan Peng , Christian Sohler

We demonstrate that for expander graphs, for all $\epsilon > 0,$ there exists a data structure of size $\widetilde{O}(n\epsilon^{-1})$ which can be used to return $(1 + \epsilon)$-approximations to effective resistances in…

Data Structures and Algorithms · Computer Science 2022-11-04 Lawrence Li , Sushant Sachdeva

For a graph $G$ on $n$ vertices, naively sampling the position of a random walk of at time $t$ requires work $\Omega(t)$. We desire local access algorithms supporting $\text{position}(G,s,t)$ queries, which return the position of a random…

Data Structures and Algorithms · Computer Science 2021-02-16 Amartya Shankha Biswas , Edward Pyne , Ronitt Rubinfeld

Among the most important graph parameters is the Diameter, the largest distance between any two vertices. There are no known very efficient algorithms for computing the Diameter exactly. Thus, much research has been devoted to how fast this…

Data Structures and Algorithms · Computer Science 2021-03-31 Arturs Backurs , Liam Roditty , Gilad Segal , Virginia Vassilevska Williams , Nicole Wein
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