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We contribute an approach to the problem of locally computing sparse connected subgraphs of dense graphs. In this setting, given an edge in a connected graph $G = (V, E)$, an algorithm locally decides its membership in a sparse connected…

Data Structures and Algorithms · Computer Science 2020-07-13 Rogers Epstein

We introduce the $st$-cut version the Sparsest-Cut problem, where the goal is to find a cut of minimum sparsity among those separating two distinguished vertices $s,t\in V$. Clearly, this problem is at least as hard as the usual (non-$st$)…

Data Structures and Algorithms · Computer Science 2016-09-26 Robert Krauthgamer , Tal Wagner

We present improved algorithms for short cycle decomposition of a graph. Short cycle decompositions were introduced in the recent work of Chu et al, and were used to make progress on several questions in graph sparsification. For all…

Data Structures and Algorithms · Computer Science 2019-01-15 Yang P. Liu , Sushant Sachdeva , Zejun Yu

In this paper we address the problem of computing a sparse subgraph of a weighted directed graph such that the exact distances from a designated source vertex to all other vertices are preserved under bounded weight increment. Finding a…

Data Structures and Algorithms · Computer Science 2017-07-18 Diptarka Chakraborty , Debarati Das

The significant progress in constructing graph spanners that are sparse (small number of edges) or light (low total weight) has skipped spanners that are everywhere-sparse (small maximum degree). This disparity is in line with other network…

Data Structures and Algorithms · Computer Science 2012-05-02 Eden Chlamtac , Michael Dinitz , Robert Krauthgamer

Sketching and streaming algorithms are in the forefront of current research directions for cut problems in graphs. In the streaming model, we show that $(1-\epsilon)$-approximation for Max-Cut must use $n^{1-O(\epsilon)}$ space; moreover,…

Data Structures and Algorithms · Computer Science 2026-02-23 Dmitry Kogan , Robert Krauthgamer

Finding dense subgraphs is a fundamental algorithmic tool in data mining, community detection, and clustering. In this problem, one aims to find an induced subgraph whose edge-to-vertex ratio is maximized. We study the directed case of this…

Data Structures and Algorithms · Computer Science 2023-11-21 Slobodan Mitrović , Theodore Pan

Stochastic optimization algorithms update models with cheap per-iteration costs sequentially, which makes them amenable for large-scale data analysis. Such algorithms have been widely studied for structured sparse models where the sparsity…

Machine Learning · Computer Science 2019-05-10 Baojian Zhou , Feng Chen , Yiming Ying

This paper presents near-optimal deterministic parallel and distributed algorithms for computing $(1+\varepsilon)$-approximate single-source shortest paths in any undirected weighted graph. On a high level, we deterministically reduce this…

Data Structures and Algorithms · Computer Science 2022-09-26 Václav Rozhoň , Christoph Grunau , Bernhard Haeupler , Goran Zuzic , Jason Li

A motif is a frequently occurring subgraph of a given directed or undirected graph $G$. Motifs capture higher order organizational structure of $G$ beyond edge relationships, and, therefore, have found wide applications such as in graph…

Data Structures and Algorithms · Computer Science 2022-09-13 Michael Kapralov , Mikhail Makarov , Sandeep Silwal , Christian Sohler , Jakab Tardos

We describe a simple algorithm for spectral graph sparsification, based on iterative computations of weighted spanners and uniform sampling. Leveraging the algorithms of Baswana and Sen for computing spanners, we obtain the first…

Data Structures and Algorithms · Computer Science 2014-04-21 Ioannis Koutis

Good approximations have been attained for the sparsest cut problem by rounding solutions to convex relaxations via low-distortion metric embeddings. Recently, Bryant and Tupper showed that this approach extends to the hypergraph setting by…

Data Structures and Algorithms · Computer Science 2023-03-09 Adam D. Jozefiak , F. Bruce Shepherd

The celebrated Cheeger's Inequality establishes a bound on the edge expansion of a graph via its spectrum. This inequality is central to a rich spectral theory of graphs, based on studying the eigenvalues and eigenvectors of the adjacency…

Discrete Mathematics · Computer Science 2016-05-06 T-H. Hubert Chan , Anand Louis , Zhihao Gavin Tang , Chenzi Zhang

A cut $\varepsilon$-sparsifier of a weighted graph $G$ is a re-weighted subgraph of $G$ of (quasi)linear size that preserves the size of all cuts up to a multiplicative factor of $\varepsilon$. Since their introduction by Bencz\'ur and…

Data Structures and Algorithms · Computer Science 2020-03-25 Silvia Butti , Stanislav Zivny

In the Single Source Replacement Paths (SSRP) problem we are given a graph $G = (V, E)$, and a shortest paths tree $\widehat{K}$ rooted at a node $s$, and the goal is to output for every node $t \in V$ and for every edge $e$ in…

Data Structures and Algorithms · Computer Science 2020-04-29 Shiri Chechik , Ofer Magen

We study distributed algorithms built around minor-based vertex sparsifiers, and give the first algorithm in the CONGEST model for solving linear systems in graph Laplacian matrices to high accuracy. Our Laplacian solver has a round…

Data Structures and Algorithms · Computer Science 2022-02-08 Sebastian Forster , Gramoz Goranci , Yang P. Liu , Richard Peng , Xiaorui Sun , Mingquan Ye

We present several sparsification lower and upper bounds for classic problems in graph theory and logic. For the problems 4-Coloring, (Directed) Hamiltonian Cycle, and (Connected) Dominating Set, we prove that there is no polynomial-time…

Computational Complexity · Computer Science 2015-09-25 Bart M. P. Jansen , Astrid Pieterse

In the decremental single-source shortest paths (SSSP) problem we want to maintain the distances between a given source node $s$ and every other node in an $n$-node $m$-edge graph $G$ undergoing edge deletions. While its static counterpart…

Data Structures and Algorithms · Computer Science 2018-08-20 Monika Henzinger , Sebastian Krinninger , Danupon Nanongkai

This paper presents the first parallel batch-dynamic algorithms for computing spanners and sparsifiers. Our algorithms process any batch of edge insertions and deletions in an $n$-node undirected graph, in $\text{poly}(\log n)$ depth and…

Data Structures and Algorithms · Computer Science 2025-07-10 Mohsen Ghaffari , Jaehyun Koo

The interconnectedness and interdependence of modern graphs are growing ever more complex, causing enormous resources for processing, storage, communication, and decision-making of these graphs. In this work, we focus on the task graph…

Machine Learning · Computer Science 2023-01-16 Ryan Wickman , Xiaofei Zhang , Weizi Li