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Motivated by the problem of routing reliably and scalably in a graph, we introduce the notion of a splicer, the union of spanning trees of a graph. We prove that for any bounded-degree n-vertex graph, the union of two random spanning trees…

Discrete Mathematics · Computer Science 2008-07-10 Navin Goyal , Luis Rademacher , Santosh Vempala

The $k$-cut problem asks, given a connected graph $G$ and a positive integer $k$, to find a minimum-weight set of edges whose removal splits $G$ into $k$ connected components. We give the first polynomial-time algorithm with approximation…

Data Structures and Algorithms · Computer Science 2018-11-12 MohammadHossein Bateni , Alireza Farhadi , MohammadTaghi Hajiaghayi

In a breakthrough work, Kawarabayashi and Thorup (J.~ACM'19) gave a near-linear time deterministic algorithm for minimum cut in a simple graph $G = (V,E)$. A key component is finding the $(1+\varepsilon)$-KT partition of $G$, the coarsest…

Data Structures and Algorithms · Computer Science 2021-11-03 Simon Apers , Paweł Gawrychowski , Troy Lee

For an undirected edge-weighted graph $G$ and a set $R$ of pairs of vertices called pairs of terminals, a multicut is a set of edges such that removing these edges from $G$ disconnects each pair in $R$. We provide an algorithm computing a…

Data Structures and Algorithms · Computer Science 2020-10-06 Vincent Cohen-Addad , Éric Colin de Verdière , Arnaud de Mesmay

We present a very simple and intuitive algorithm to find balanced sparse cuts in a graph via shortest-paths. Our algorithm combines a new multiplicative-weights framework for solving unit-weight multi-commodity flows with standard ball…

Data Structures and Algorithms · Computer Science 2022-09-20 Li Chen , Rasmus Kyng , Maximilian Probst Gutenberg , Sushant Sachdeva

In the non-uniform sparsest cut problem, we are given a supply graph G and a demand graph D, both with the same set of nodes V. The goal is to find a cut of V that minimizes the ratio of the total capacity on the edges of G crossing the cut…

Data Structures and Algorithms · Computer Science 2021-11-12 Vincent Cohen-Addad , Tobias Mömke , Victor Verdugo

For many popular graph metric sparsifiers, such as spanners, emulators, and preservers, simple and elegant greedy algorithms are known that achieve state-of-the-art or existentially optimal tradeoffs between size and quality. The goal of…

Data Structures and Algorithms · Computer Science 2026-04-28 Ben Bals , Joakim Blikstad , Greg Bodwin , Daniel Dadush , Sebastian Forster , Yasamin Nazari

We give almost-linear-time algorithms for approximating rooted minimum cut and maximum arborescence packing in directed graphs, two problems that are dual to each other [Edm73]. More specifically, for an $n$-vertex, $m$-edge directed graph…

Data Structures and Algorithms · Computer Science 2025-12-18 Yonggang Jiang , Yaowei Long , Thatchaphol Saranurak , Benyu Wang

Given a directed graph $G$, a transitive reduction $G^t$ of $G$ (first studied by Aho, Garey, Ullman [SICOMP `72]) is a minimal subgraph of $G$ that preserves the reachability relation between every two vertices in $G$. In this paper, we…

Data Structures and Algorithms · Computer Science 2025-04-28 Gramoz Goranci , Adam Karczmarz , Ali Momeni , Nikos Parotsidis

We provide a simple new randomized contraction approach to the global minimum cut problem for simple undirected graphs. The contractions exploit 2-out edge sampling from each vertex rather than the standard uniform edge sampling. We…

Data Structures and Algorithms · Computer Science 2019-09-04 Mohsen Ghaffari , Krzysztof Nowicki , Mikkel Thorup

We study the Requirement Cut problem, a generalization of numerous classical graph partitioning problems including Multicut, Multiway Cut, $k$-Cut, and Steiner Multicut among others. Given a graph with edge costs, terminal groups $(S_1,…

Data Structures and Algorithms · Computer Science 2025-11-25 Nadym Mallek , Kirill Simonov

Graph Neural Networks (GNNs) have demonstrated superior performance across various graph learning tasks but face significant computational challenges when applied to large-scale graphs. One effective approach to mitigate these challenges is…

Machine Learning · Computer Science 2024-10-04 Guibin Zhang , Xiangguo Sun , Yanwei Yue , Chonghe Jiang , Kun Wang , Tianlong Chen , Shirui Pan

This paper presents efficient distributed algorithms for a number of fundamental problems in the area of graph sparsification: We provide the first deterministic distributed algorithm that computes an ultra-sparse spanner in…

Data Structures and Algorithms · Computer Science 2022-09-26 Marcel Bezdrighin , Michael Elkin , Mohsen Ghaffari , Christoph Grunau , Bernhard Haeupler , Saeed Ilchi , Václav Rozhoň

In this paper, we consider the problem of clustering graph nodes and sparsifying graph edges over distributed graphs, when graph edges with possibly edge duplicates are observed at physically remote sites. Although edge duplicates across…

Data Structures and Algorithms · Computer Science 2023-02-21 Chun Jiang Zhu

Spectral graph sparsification aims to find ultra-sparse subgraphs whose Laplacian matrix can well approximate the original Laplacian eigenvalues and eigenvectors. In recent years, spectral sparsification techniques have been extensively…

Data Structures and Algorithms · Computer Science 2020-04-30 Zhuo Feng

The All-Pairs Min-Cut problem (aka All-Pairs Max-Flow) asks to compute a minimum $s$-$t$ cut (or just its value) for all pairs of vertices $s,t$. We study this problem in directed graphs with unit edge/vertex capacities (corresponding to…

For any undirected graph $G=(V,E)$ and a set $E_W$ of candidate edges with $E\cap E_W=\emptyset$, the $(k,\gamma)$-spectral augmentability problem is to find a set $F$ of $k$ edges from $E_W$ with appropriate weighting, such that the…

Data Structures and Algorithms · Computer Science 2020-06-26 Bogdan-Adrian Manghiuc , Pan Peng , He Sun

We present a universally-optimal distributed algorithm for the exact weighted min-cut. The algorithm is guaranteed to complete in $\widetilde{O}(D + \sqrt{n})$ rounds on every graph, recovering the recent result of Dory, Efron,…

Data Structures and Algorithms · Computer Science 2022-06-01 Mohsen Ghaffari , Goran Zuzic

We consider the semi-random graph model of [Makarychev, Makarychev and Vijayaraghavan, STOC'12], where, given a random bipartite graph with $\alpha$ edges and an unknown bipartition $(A, B)$ of the vertex set, an adversary can add arbitrary…

Data Structures and Algorithms · Computer Science 2024-06-10 Vincent Cohen-Addad , Tommaso d'Orsi , Aida Mousavifar

Thin spanning trees lie at the intersection of graph theory, approximation algorithms, and combinatorial optimization. They are central to the long-standing \emph{thin tree conjecture}, which asks whether every $k$-edge-connected graph…

Data Structures and Algorithms · Computer Science 2025-10-15 Mohit Daga