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We design new algorithms for approximating 2CSPs on graphs with bounded threshold rank, that is, whose normalized adjacency matrix has few eigenvalues larger than $\varepsilon$, smaller than $-\varepsilon$, or both. Unlike on worst-case…

Data Structures and Algorithms · Computer Science 2025-11-17 Prashanti Anderson , Samuel B. Hopkins , Amit Rajaraman , David Steurer

Given a directed graph $G = (V,E)$, undergoing an online sequence of edge deletions with $m$ edges in the initial version of $G$ and $n = |V|$, we consider the problem of maintaining all-pairs shortest paths (APSP) in $G$. Whilst this…

Data Structures and Algorithms · Computer Science 2020-10-05 Jacob Evald , Viktor Fredslund-Hansen , Maximilian Probst Gutenberg , Christian Wulff-Nilsen

An emerging trend in approximate counting is to show that certain `low-temperature' problems are easy on typical instances, despite worst-case hardness results. For the class of regular graphs one usually shows that expansion can be…

Data Structures and Algorithms · Computer Science 2024-02-06 Charles Carlson , Ewan Davies , Alexandra Kolla

We design fast deterministic algorithms for distance computation in the congested clique model. Our key contributions include: -- A $(2+\epsilon)$-approximation for all-pairs shortest paths in $O(\log^2{n} / \epsilon)$ rounds on unweighted…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-11-01 Keren Censor-Hillel , Michal Dory , Janne H. Korhonen , Dean Leitersdorf

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

We present a general method of designing fast approximation algorithms for cut-based minimization problems in undirected graphs. In particular, we develop a technique that given any such problem that can be approximated quickly on trees,…

Data Structures and Algorithms · Computer Science 2010-11-09 Aleksander Madry

We consider the all pairs all shortest paths (APASP) problem, which maintains the shortest path dag rooted at every vertex in a directed graph G=(V,E) with positive edge weights. For this problem we present a decremental algorithm (that…

Data Structures and Algorithms · Computer Science 2014-11-18 Meghana Nasre , Matteo Pontecorvi , Vijaya Ramachandran

The radius and diameter are fundamental graph parameters. They are defined as the minimum and maximum of the eccentricities in a graph, respectively, where the eccentricity of a vertex is the largest distance from the vertex to another…

Data Structures and Algorithms · Computer Science 2015-06-08 Amir Abboud , Virginia Vassilevska Williams , Joshua Wang

We initiate the study of approximating the largest induced expander in a given graph $G$. Given a $\Delta$-regular graph $G$ with $n$ vertices, the goal is to find the set with the largest induced expansion of size at least $\delta \cdot…

Data Structures and Algorithms · Computer Science 2015-11-10 Shayan Oveis Gharan , Alireza Rezaei

The diameter, radius and eccentricities are natural graph parameters. While these problems have been studied extensively, there are no known dynamic algorithms for them beyond the ones that follow from trivial recomputation after each…

Data Structures and Algorithms · Computer Science 2019-12-18 Bertie Ancona , Monika Henzinger , Liam Roditty , Virginia Vassilevska Williams , Nicole Wein

We study deterministic algorithms for computing graph cuts, with focus on two fundamental problems: balanced sparse cut and $k$-vertex connectivity for small $k$ ($k=O(\polylog n)$). Both problems can be solved in near-linear time with…

Data Structures and Algorithms · Computer Science 2019-10-21 Yu Gao , Jason Li , Danupon Nanongkai , Richard Peng , Thatchaphol Saranurak , Sorrachai Yingchareonthawornchai

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

Graphs are fundamental objects that find widespread applications across computer science and beyond. Graph Theory has yielded deep insights about structural properties of various families of graphs, which are leveraged in the design and…

Data Structures and Algorithms · Computer Science 2023-08-30 Rachit Nimavat

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 at most $\epsilon m$…

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

A $t$-spanner of an undirected $n$-vertex graph $G$ is a sparse subgraph $H$ of $G$ that preserves all pairwise distances between its vertices to within multiplicative factor $t$, also called the \emph{stretch}. We investigate the problem…

Data Structures and Algorithms · Computer Science 2026-01-29 Julia Chuzhoy , Merav Parter

We provide a new constant factor approximation algorithm for the (connected) distance-$r$ dominating set problem on graph classes of bounded expansion. Classes of bounded expansion include many familiar classes of sparse graphs such as…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-06-08 Saeed Akhoondian Amiri , Patrice Ossona de Mendez , Roman Rabinovich , Sebastian Siebertz

Approximate subgraph matching (ASM) is a task that determines the approximate presence of a given query graph in a large target graph. Being an NP-hard problem, ASM is critical in graph analysis with a myriad of applications ranging from…

Machine Learning · Computer Science 2026-03-20 Kaiyang Li , Shihao Ji , Zhipeng Cai , Wei Li

The graph is one of the most widely used mathematical structures in engineering and science because of its representational power and inherent ability to demonstrate the relationship between objects. The objective of this work is to…

Data Structures and Algorithms · Computer Science 2021-01-01 Shri Prakash Dwivedi

In recent years, the expander decomposition method was used to develop many graph algorithms, resulting in major improvements to longstanding complexity barriers. This powerful hammer has led the community to (1) believe that most problems…

Data Structures and Algorithms · Computer Science 2022-11-28 Amir Abboud , Nathan Wallheimer