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We consider the problem of finding a minimum cut of a weighted graph presented as a single-pass stream. While graph sparsification in streams has been intensively studied, the specific application of finding minimum cuts in streams is less…

Data Structures and Algorithms · Computer Science 2024-12-09 Matthew Ding , Alexandro Garces , Jason Li , Honghao Lin , Jelani Nelson , Vihan Shah , David P. Woodruff

We present a data stream algorithm for estimating the size of the maximum matching of a low arboricity graph. Recall that a graph has arboricity $\alpha$ if its edges can be partitioned into at most $\alpha$ forests and that a planar graph…

Data Structures and Algorithms · Computer Science 2017-08-15 Andrew McGregor , Sofya Vorotnikova

We describe approximation algorithms in Linial's classic LOCAL model of distributed computing to find maximum-weight matchings in a hypergraph of rank $r$. Our main result is a deterministic algorithm to generate a matching which is an…

Data Structures and Algorithms · Computer Science 2023-10-13 David G. Harris

We consider the maximum matching problem in the semi-streaming model formalized by Feigenbaum, Kannan, McGregor, Suri, and Zhang that is inspired by giant graphs of today. As our main result, we give a two-pass $(1/2 + 1/16)$-approximation…

Data Structures and Algorithms · Computer Science 2017-04-24 Sagar Kale , Sumedh Tirodkar

We present streaming algorithms for the graph $k$-matching problem in both the insert-only and dynamic models. Our algorithms, with space complexity matching the best upper bounds, have optimal or near-optimal update time, significantly…

Data Structures and Algorithms · Computer Science 2023-10-18 Jianer Chen , Qin Huang , Iyad Kanj , Qian Li , Ge Xia

Calculating the diameter of an undirected graph requires quadratic running time under the Strong Exponential Time Hypothesis and this barrier works even against any approximation better than 3/2. For planar graphs with positive edge…

Data Structures and Algorithms · Computer Science 2025-07-08 Michał Włodarczyk

Recently [Bhattacharya et al., STOC 2015] provide the first non-trivial algorithm for the densest subgraph problem in the streaming model with additions and deletions to its edges, i.e., for dynamic graph streams. They present a…

Data Structures and Algorithms · Computer Science 2015-07-30 Hossein Esfandiari , MohammadTaghi Hajiaghayi , David P. Woodruff

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 study the problem of graph and hypergraph sparsification in insertion-only data streams. The input is a hypergraph $H=(V, E, w)$ with $n$ nodes, $m$ hyperedges, and rank $r$, and the goal is to compute a hypergraph $\widehat{H}$ that…

Data Structures and Algorithms · Computer Science 2025-10-22 Vincent Cohen-Addad , David P. Woodruff , Shenghao Xie , Samson Zhou

The random order graph streaming model has received significant attention recently, with problems such as matching size estimation, component counting, and the evaluation of bounded degree constant query testable properties shown to admit…

Data Structures and Algorithms · Computer Science 2021-12-15 John Kallaugher , Michael Kapralov , Eric Price

We study learning-augmented streaming algorithms for estimating the value of MAX-CUT in a graph. In the classical streaming model, while a $1/2$-approximation for estimating the value of MAX-CUT can be trivially achieved with $O(1)$ words…

Data Structures and Algorithms · Computer Science 2025-01-07 Yinhao Dong , Pan Peng , Ali Vakilian

Counting the number of triangles in a graph has many important applications in network analysis. Several frequently computed metrics like the clustering coefficient and the transitivity ratio need to count the number of triangles in the…

Data Structures and Algorithms · Computer Science 2013-04-24 Mostafa Haghir Chehreghani

There has been a recent explosion in the size of stored data, partially due to advances in storage technology, and partially due to the growing popularity of cloud-computing and the vast quantities of data generated. This motivates the need…

Data Structures and Algorithms · Computer Science 2012-12-06 Isabelle Stanton

In the semi-streaming model, an algorithm must process any $n$-vertex graph by making one or few passes over a stream of its edges, use $O(n \cdot \text{polylog }n)$ words of space, and at the end of the last pass, output a solution to the…

Data Structures and Algorithms · Computer Science 2025-10-23 Sepehr Assadi , Gary Hoppenworth , Janani Sundaresan

We propose two one-pass streaming algorithms for the $\mathcal{NP}$-hard hypergraph matching problem. The first algorithm stores a small subset of potential matching edges in a stack using dual variables to select edges. It has an…

Data Structures and Algorithms · Computer Science 2025-07-09 Henrik Reinstädtler , S M Ferdous , Alex Pothen , Bora Uçar , Christian Schulz

We improve on random sampling techniques for approximately solving problems that involve cuts and flows in graphs. We give a near-linear-time construction that transforms any graph on n vertices into an O(n\log n)-edge graph on the same…

Data Structures and Algorithms · Computer Science 2007-05-23 Andras Benczur , David R. Karger

We consider the problem of estimating the value of max cut in a graph in the streaming model of computation. At one extreme, there is a trivial $2$-approximation for this problem that uses only $O(\log n)$ space, namely, count the number of…

Data Structures and Algorithms · Computer Science 2014-09-09 Michael Kapralov , Sanjeev Khanna , Madhu Sudan

We consider the \textsf{Unit Interval Selection} problem in the one-pass random order streaming model. Here, an algorithm is presented a sequence of $n$ unit-length intervals on the line that arrive in uniform random order, and the…

Data Structures and Algorithms · Computer Science 2026-03-11 Cezar-Mihail Alexandru , Adithya Diddapur , Magnús M. Halldórsson , Christian Konrad , Kheeran K. Naidu

We present an algorithm that, with high probability, generates a random spanning tree from an edge-weighted undirected graph in $\tilde{O}(n^{4/3}m^{1/2}+n^{2})$ time (The $\tilde{O}(\cdot)$ notation hides $\operatorname{polylog}(n)$…

Data Structures and Algorithms · Computer Science 2017-06-22 David Durfee , Rasmus Kyng , John Peebles , Anup B. Rao , Sushant Sachdeva

We show an $\widetilde{O}(m^{1.5} \epsilon^{-1})$ time algorithm that on a graph with $m$ edges and $n$ vertices outputs its spanning tree count up to a multiplicative $(1+\epsilon)$ factor with high probability, improving on the previous…

Data Structures and Algorithms · Computer Science 2025-05-21 Yang P. Liu , Richard Peng , Junzhao Yang