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Baswana, Gupta and Sen [FOCS'11] showed that fully dynamic maximal matching can be maintained in general graphs with logarithmic amortized update time. More specifically, starting from an empty graph on $n$ fixed vertices, they devised a…

Data Structures and Algorithms · Computer Science 2016-04-29 Shay Solomon

A maximal independent set (MIS) can be maintained in an evolving $m$-edge graph by simply recomputing it from scratch in $O(m)$ time after each update. But can it be maintained in time sublinear in $m$ in fully dynamic graphs? We answer…

Data Structures and Algorithms · Computer Science 2018-02-28 Sepehr Assadi , Krzysztof Onak , Baruch Schieber , Shay Solomon

Maintaining maximal independent set in dynamic graph is a fundamental open problem in graph theory and the first sublinear time deterministic algorithm was came up by Assadi, Onak, Schieber and Solomon(STOC'18), which achieves $O(m^{3/4})$…

Data Structures and Algorithms · Computer Science 2018-04-25 Yuhao Du , Hengjie Zhang

We present faster algorithms for approximate maximum flow in undirected graphs with good separator structures, such as bounded genus, minor free, and geometric graphs. Given such a graph with $n$ vertices, $m$ edges along with a recursive…

Data Structures and Algorithms · Computer Science 2012-10-19 Gary Miller , Richard Peng

We present the first data structures that maintain near optimal maximum cardinality and maximum weighted matchings on sparse graphs in sublinear time per update. Our main result is a data structure that maintains a $(1+\epsilon)$…

Data Structures and Algorithms · Computer Science 2013-04-11 Manoj Gupta , Richard Peng

We give a fully dynamic deterministic algorithm for maintaining a maximal matching of an $n$-vertex graph in $\tilde{O}(n^{8/9})$ amortized update time. This breaks the long-standing $\Omega(n)$-update-time barrier on dense graphs,…

Data Structures and Algorithms · Computer Science 2025-09-01 Aaron Bernstein , Sayan Bhattacharya , Peter Kiss , Thatchaphol Saranurak

Graph sparsification is a powerful tool to approximate an arbitrary graph and has been used in machine learning over homogeneous graphs. In heterogeneous graphs such as knowledge graphs, however, sparsification has not been systematically…

Machine Learning · Computer Science 2022-11-15 Chandan Chunduru , Chun Jiang Zhu , Blake Gains , Jinbo Bi

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

Recently we presented the first algorithm for maintaining the set of nodes reachable from a source node in a directed graph that is modified by edge deletions with $o(mn)$ total update time, where $m$ is the number of edges and $n$ is the…

Data Structures and Algorithms · Computer Science 2016-12-13 Monika Henzinger , Sebastian Krinninger , Danupon Nanongkai

In this paper we devise an extremely efficient fully dynamic distributed algorithm for maintaining sparse spanners. Our resuls also include the first fully dynamic centralized algorithm for the problem with non-trivial bounds for both…

Data Structures and Algorithms · Computer Science 2009-09-29 Michael Elkin

In this paper, we consider the problem of designing cut sparsifiers and sketches for directed graphs. To bypass known lower bounds, we allow the sparsifier/sketch to depend on the balance of the input graph, which smoothly interpolates…

Data Structures and Algorithms · Computer Science 2021-05-13 Ruoxu Cen , Yu Cheng , Debmalya Panigrahi , Kevin Sun

In this paper, we revisit spectral sparsification for sums of arbitrary positive semidefinite (PSD) matrices. Concretely, for any collection of PSD matrices $\mathcal{A} = \{A_1, A_2, \ldots, A_r\} \subset \mathbb{R}^{n \times n}$, given…

Data Structures and Algorithms · Computer Science 2026-01-05 Arpon Basu , Pravesh K. Kothari , Yang P. Liu , Raghu Meka

We show variants of spectral sparsification routines can preserve the total spanning tree counts of graphs, which by Kirchhoff's matrix-tree theorem, is equivalent to determinant of a graph Laplacian minor, or equivalently, of any SDDM…

Data Structures and Algorithms · Computer Science 2017-05-03 David Durfee , John Peebles , Richard Peng , Anup B. Rao

We give a deterministic, nearly logarithmic-space algorithm for mild spectral sparsification of undirected graphs. Given a weighted, undirected graph $G$ on $n$ vertices described by a binary string of length $N$, an integer $k\leq \log n$,…

Data Structures and Algorithms · Computer Science 2020-04-21 Dean Doron , Jack Murtagh , Salil Vadhan , David Zuckerman

The eigendeomposition of nearest-neighbor (NN) graph Laplacian matrices is the main computational bottleneck in spectral clustering. In this work, we introduce a highly-scalable, spectrum-preserving graph sparsification algorithm that…

Machine Learning · Computer Science 2018-10-12 Yongyu Wang , Zhuo Feng

We give the first fully dynamic algorithm which maintains a $(1-\epsilon)$-approximate densest subgraph in worst-case time $\text{poly}(\log n, \epsilon^{-1})$ per update. Dense subgraph discovery is an important primitive for many…

Data Structures and Algorithms · Computer Science 2020-03-12 Saurabh Sawlani , Junxing Wang

We show how to find and efficiently maintain maximal k-edge-connected subgraphs in undirected graphs. In particular, we provide the following results. (1) A general framework for maintaining the maximal k-edge-connected subgraphs upon…

Data Structures and Algorithms · Computer Science 2023-05-02 Loukas Georgiadis , Giuseppe F. Italiano , Evangelos Kosinas , Debasish Pattanayak

We develop a framework for graph sparsification and sketching, based on a new tool, short cycle decomposition -- a decomposition of an unweighted graph into an edge-disjoint collection of short cycles, plus few extra edges. A simple…

Data Structures and Algorithms · Computer Science 2018-05-31 Timothy Chu , Yu Gao , Richard Peng , Sushant Sachdeva , Saurabh Sawlani , Junxing Wang

We provide an algorithm that, given an $n$-vertex $m$-edge Eulerian graph with polynomially bounded weights, computes an $\breve{O}(n\log^{2} n \cdot \varepsilon^{-2})$-edge $\varepsilon$-approximate Eulerian sparsifier with high…

Data Structures and Algorithms · Computer Science 2024-08-20 Arun Jambulapati , Sushant Sachdeva , Aaron Sidford , Kevin Tian , Yibin Zhao

We present an algorithm that on input of an $n$-vertex $m$-edge weighted graph $G$ and a value $k$, produces an {\em incremental sparsifier} $\hat{G}$ with $n-1 + m/k$ edges, such that the condition number of $G$ with $\hat{G}$ is bounded…

Data Structures and Algorithms · Computer Science 2015-03-13 Ioannis Koutis , Gary L. Miller , Richard Peng
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