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Consider an undirected weighted graph $G = (V,E,w)$. We study the problem of computing $(1+\epsilon)$-approximate shortest paths for $S \times V$, for a subset $S \subseteq V$ of $|S| = n^r$ sources, for some $0 < r \le 1$. We devise a…

Data Structures and Algorithms · Computer Science 2021-02-15 Michael Elkin , Ofer Neiman

In this work, we present the first algorithm to compute expander decompositions in an m-edge directed graph with near-optimal time \~O(m). Further, our algorithm can maintain such a decomposition in a dynamic graph and again obtains…

Data Structures and Algorithms · Computer Science 2025-02-12 Aurelio L. Sulser , Maximilian Probst Gutenberg

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 consider the distributed and parallel construction of low-diameter decompositions with strong diameter for (weighted) graphs and (weighted) graphs that can be separated through $k \in \tilde{O}(1)$ shortest paths. This class of graphs…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-12-02 Jinfeng Dou , Thorsten Götte , Henning Hillebrandt , Christian Scheideler , Julian Werthmann

We develop a novel parallel decomposition strategy for unweighted, undirected graphs, based on growing disjoint connected clusters from batches of centers progressively selected from yet uncovered nodes. With respect to similar previous…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-02-09 Matteo Ceccarello , Andrea Pietracaprina , Geppino Pucci , Eli Upfal

Diffusion is a fundamental graph procedure and has been a basic building block in a wide range of theoretical and empirical applications such as graph partitioning and semi-supervised learning on graphs. In this paper, we study…

Data Structures and Algorithms · Computer Science 2021-06-07 Li Chen , Richard Peng , Di Wang

We present an algorithm that given a linear program with $n$ variables, $m$ constraints, and constraint matrix $A$, computes an $\epsilon$-approximate solution in $\tilde{O}(\sqrt{rank(A)}\log(1/\epsilon))$ iterations with high probability.…

Data Structures and Algorithms · Computer Science 2020-09-02 Yin Tat Lee , Aaron Sidford

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 present fast algorithms for approximate shortest paths in the massively parallel computation (MPC) model. We provide randomized algorithms that take $poly(\log{\log{n}})$ rounds in the near-linear memory MPC model. Our results are for…

Data Structures and Algorithms · Computer Science 2025-05-20 Michal Dory , Shaked Matar

This paper bridges discrete and continuous optimization approaches for decomposable submodular function minimization, in both the standard and parametric settings. We provide improved running times for this problem by reducing it to a…

Data Structures and Algorithms · Computer Science 2021-03-08 Kyriakos Axiotis , Adam Karczmarz , Anish Mukherjee , Piotr Sankowski , Adrian Vladu

In the $k$-edge-connected spanning subgraph ($k$ECSS) problem, our goal is to compute a minimum-cost sub-network that is resilient against up to $k$ link failures: Given an $n$-node $m$-edge graph with a cost function on the edges, our goal…

We present faster high-accuracy algorithms for computing $\ell_p$-norm minimizing flows. On a graph with $m$ edges, our algorithm can compute a $(1+1/\text{poly}(m))$-approximate unweighted $\ell_p$-norm minimizing flow with…

Data Structures and Algorithms · Computer Science 2020-01-10 Deeksha Adil , Sushant Sachdeva

In this paper, we develop an $O((m \log k) {\rm MSF} (n,m,1))$-time algorithm to find a half-integral node-capacitated multiflow of the maximum total flow-value in a network with $n$ nodes, $m$ edges, and $k$ terminals, where ${\rm MSF}…

Data Structures and Algorithms · Computer Science 2018-10-30 Hiroshi Hirai

Depth first search (DFS) tree is a fundamental data structure for solving graph problems. The classical algorithm [SiComp74] for building a DFS tree requires $O(m+n)$ time for a given graph $G$ having $n$ vertices and $m$ edges. Recently,…

Data Structures and Algorithms · Computer Science 2017-05-11 Shahbaz Khan

We investigate the time-complexity of the All-Pairs Max-Flow problem: Given a graph with $n$ nodes and $m$ edges, compute for all pairs of nodes the maximum-flow value between them. If Max-Flow (the version with a given source-sink pair…

Data Structures and Algorithms · Computer Science 2019-07-11 Amir Abboud , Robert Krauthgamer , Ohad Trabelsi

We provide evidence that computing the maximum flow value between every pair of nodes in a directed graph on $n$ nodes, $m$ edges,and capacities in the range $[1..n]$, which we call the All-Pairs Max-Flow problem, cannot be solved in time…

Data Structures and Algorithms · Computer Science 2022-11-22 Robert Krauthgamer , Ohad Trabelsi

Maximum bipartite matching (MBM) is a fundamental problem in combinatorial optimization with a long and rich history. A classic result of Hopcroft and Karp (1973) provides an $O(m \sqrt{n})$-time algorithm for the problem, where $n$ and $m$…

Data Structures and Algorithms · Computer Science 2024-06-03 Julia Chuzhoy , Sanjeev Khanna

Motivated by the increasing need to understand the algorithmic foundations of distributed large-scale graph computations, we study a number of fundamental graph problems in a message-passing model for distributed computing where $k \geq 2$…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-07-07 Gopal Pandurangan , Peter Robinson , Michele Scquizzato

We give a deterministic algorithm for computing a global minimum vertex cut in a vertex-weighted graph $n$ vertices and $m$ edges in $\widehat O(mn)$ time. This breaks the long-standing $\widehat \Omega(n^{4})$-time barrier in dense graphs,…

Data Structures and Algorithms · Computer Science 2025-03-28 Yonggang Jiang , Chaitanya Nalam , Thatchaphol Saranurak , Sorrachai Yingchareonthawornchai

We give an $\tilde{O}(n^{7/5} \log (nC))$-time algorithm to compute a minimum-cost maximum cardinality matching (optimal matching) in $K_h$-minor free graphs with $h=O(1)$ and integer edge weights having magnitude at most $C$. This improves…

Data Structures and Algorithms · Computer Science 2018-07-16 Nathaniel Lahn , Sharath Raghvendra
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