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Expander decompositions have become one of the central frameworks in the design of fast algorithms. For an undirected graph $G=(V,E)$, a near-optimal $\phi$-expander decomposition is a partition $V_1, V_2, \ldots, V_k$ of the vertex set $V$…

Data Structures and Algorithms · Computer Science 2025-01-07 Daoyuan Chen , Simon Meierhans , Maximilian Probst Gutenberg , Thatchaphol Saranurak

Expander decompositions form the basis of one of the most flexible paradigms for close-to-linear-time graph algorithms. Length-constrained expander decompositions generalize this paradigm to better work for problems with lengths, distances…

Data Structures and Algorithms · Computer Science 2024-05-16 Bernhard Haeupler , D Ellis Hershkowitz , Zihan Tan

We study the problem of graph clustering where the goal is to partition a graph into clusters, i.e. disjoint subsets of vertices, such that each cluster is well connected internally while sparsely connected to the rest of the graph. In…

Data Structures and Algorithms · Computer Science 2021-12-17 Thatchaphol Saranurak , Di Wang

An $(\epsilon,\phi)$-expander decomposition of a graph $G=(V,E)$ is a clustering of the vertices $V=V_{1}\cup\cdots\cup V_{x}$ such that (1) each cluster $V_{i}$ induces subgraph with conductance at least $\phi$, and (2) the number of…

Data Structures and Algorithms · Computer Science 2019-05-28 Yi-Jun Chang , Thatchaphol Saranurak

In this paper we study the problem of finding $(\epsilon, \phi)$-expander decompositions of a graph in the streaming model, in particular for dynamic streams of edge insertions and deletions. The goal is to partition the vertex set so that…

Data Structures and Algorithms · Computer Science 2024-05-30 Yu Chen , Michael Kapralov , Mikhail Makarov , Davide Mazzali

Length-constrained expander decompositions are a new graph decomposition that has led to several recent breakthroughs in fast graph algorithms. Roughly, an $(h, s)$-length $\phi$-expander decomposition is a small collection of length…

Data Structures and Algorithms · Computer Science 2025-10-14 Greg Bodwin , Bernhard Haeupler , D Ellis Hershkowitz , Zihan Tan

In this article, we show that the algorithm of maintaining expander decompositions in graphs undergoing edge deletions directly by removing sparse cuts repeatedly can be made efficient. Formally, for an $m$-edge undirected graph $G$, we say…

Data Structures and Algorithms · Computer Science 2023-01-24 Yiding Hua , Rasmus Kyng , Maximilian Probst Gutenberg , Zihang Wu

A $(\phi,\epsilon)$-expander-decomposition of a graph $G$ (with $n$ vertices and $m$ edges) is a partition of $V$ into clusters $V_1,\ldots,V_k$ with conductance $\Phi(G[V_i]) \ge \phi$, such that there are at most $\epsilon m$…

Data Structures and Algorithms · Computer Science 2025-02-04 Daniel Agassy , Dani Dorfman , Haim Kaplan

Expander graphs are known to be robust to edge deletions in the following sense: for any online sequence of edge deletions $e_1, e_2, \ldots, e_k$ to an $m$-edge graph $G$ that is initially a $\phi$-expander, the algorithm can grow a set $P…

Data Structures and Algorithms · Computer Science 2025-04-02 Simon Meierhans , Maximilian Probst Gutenberg , Thatchaphol Saranurak

We give an algorithm that computes exact maximum flows and minimum-cost flows on directed graphs with $m$ edges and polynomially bounded integral demands, costs, and capacities in $m^{1+o(1)}$ time. Our algorithm builds the flow through a…

Data Structures and Algorithms · Computer Science 2022-04-26 Li Chen , Rasmus Kyng , Yang P. Liu , Richard Peng , Maximilian Probst Gutenberg , Sushant Sachdeva

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

We give faster algorithms for weak expander decompositions and approximate max flow on undirected graphs. First, we show that it is possible to "warm start" the cut-matching game when computing weak expander decompositions, avoiding the…

Data Structures and Algorithms · Computer Science 2025-11-06 Henry Fleischmann , George Z. Li , Jason Li

We give the first almost-linear total time algorithm for deciding if a flow of cost at most $F$ still exists in a directed graph, with edge costs and capacities, undergoing decremental updates, i.e., edge deletions, capacity decreases, and…

Data Structures and Algorithms · Computer Science 2024-07-16 Jan van den Brand , Li Chen , Rasmus Kyng , Yang P. Liu , Simon Meierhans , Maximilian Probst Gutenberg , Sushant Sachdeva

We design efficient deterministic algorithms for finding short edge-disjoint paths in expanders. Specifically, given an $n$-vertex $m$-edge expander $G$ of conductance $\phi$ and minimum degree $\delta$, and a set of pairs $\{(s_i,t_i)\}_i$…

Data Structures and Algorithms · Computer Science 2025-11-05 Matija Bucić , Zhongtian He , Shang-En Huang , Thatchaphol Saranurak

There is a recent exciting line of work in distributed graph algorithms in the $\mathsf{CONGEST}$ model that exploit expanders. All these algorithms so far are based on two tools: expander decomposition and expander routing. An…

Data Structures and Algorithms · Computer Science 2020-07-30 Yi-Jun Chang , Thatchaphol Saranurak

In the decremental single-source shortest paths problem, the goal is to maintain distances from a fixed source $s$ to every vertex $v$ in an $m$-edge graph undergoing edge deletions. In this paper, we conclude a long line of research on…

Data Structures and Algorithms · Computer Science 2021-01-20 Aaron Bernstein , Maximilian Probst Gutenberg , Thatchaphol Saranurak

A $(\phi,\epsilon)$-expander-decomposition of a graph $G$ (with $n$ vertices and $m$ edges) is a partition of $V$ into clusters $V_1,\ldots,V_k$ with conductance $\Phi(G[V_i]) \ge \phi$, such that there are $O(\epsilon m)$ inter-cluster…

Data Structures and Algorithms · Computer Science 2025-11-20 Daniel Agassy , Dani Dorfman , Haim Kaplan

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

We bound the smoothed running time of the FLIP algorithm for local Max-Cut as a function of $\alpha$, the arboricity of the input graph. We show that, with high probability and in expectation, the following holds (where $n$ is the number of…

Data Structures and Algorithms · Computer Science 2024-04-23 Gregory Schwartzman

Expander decompositions of graphs have significantly advanced the understanding of many classical graph problems and led to numerous fundamental theoretical results. However, their adoption in practice has been hindered due to their…

Data Structures and Algorithms · Computer Science 2026-04-27 Kathrin Hanauer , Monika Henzinger , Robin Münk , Harald Räcke , Maximilian Vötsch
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