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We present an undirected version of the recently introduced flow-augmentation technique: Given an undirected multigraph $G$ with distinguished vertices $s,t \in V(G)$ and an integer $k$, one can in randomized $k^{O(1)} \cdot (|V(G)| +…

Data Structures and Algorithms · Computer Science 2023-02-16 Eun Jung Kim , Stefan Kratsch , Marcin Pilipczuk , Magnus Wahlström

The bipartite graph structure has shown its promising ability in facilitating the subspace clustering and spectral clustering algorithms for large-scale datasets. To avoid the post-processing via k-means during the bipartite graph…

Machine Learning · Computer Science 2023-05-15 Si-Guo Fang , Dong Huang , Chang-Dong Wang , Jian-Huang Lai

In the Connected Dominating Set problem we are given a graph $G=(V,E)$ and seek a minimum size dominating set $S \subseteq V$ such that the subgraph $G[S]$ of $G$ induced by $S$ is connected. In the $2$-Edge-Connected Dominating Set problem…

Data Structures and Algorithms · Computer Science 2019-12-23 Amir Belgi , Zeev Nutov

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 present a $(1+\varepsilon)$-approximate parallel algorithm for computing shortest paths in undirected graphs, achieving $\mathrm{poly}(\log n)$ depth and $m\mathrm{poly}(\log n)$ work for $n$-nodes $m$-edges graphs. Although sequential…

Data Structures and Algorithms · Computer Science 2019-11-06 Alexandr Andoni , Clifford Stein , Peilin Zhong

Low Diameter Decompositions (LDDs) are invaluable tools in the design of combinatorial graph algorithms. While historically they have been applied mainly to undirected graphs, in the recent breakthrough for the negative-length Single Source…

Data Structures and Algorithms · Computer Science 2025-02-11 Karl Bringmann , Nick Fischer , Bernhard Haeupler , Rustam Latypov

We study the allocation problem in the Massively Parallel Computation (MPC) model. This problem is a special case of $b$-matching, in which the input is a bipartite graph with capacities greater than $1$ in only one part of the bipartition.…

Data Structures and Algorithms · Computer Science 2025-06-06 Jakub Łącki , Slobodan Mitrović , Srikkanth Ramachandran , Wen-Horng Sheu

Cutwidth is one of the classic layout parameters for graphs. It measures how well one can order the vertices of a graph in a linear manner, so that the maximum number of edges between any prefix and its complement suffix is minimized. As…

Data Structures and Algorithms · Computer Science 2017-02-16 Archontia C. Giannopoulou , Michał Pilipczuk , Jean-Florent Raymond , Dimitrios M. Thilikos , Marcin Wrochna

Alon and Krivelevich (SIAM J. Discrete Math. 15(2): 211-227 (2002)) show that if a graph is {\epsilon}-far from bipartite, then the subgraph induced by a random subset of O(1/{\epsilon}) vertices is bipartite with high probability. We…

Data Structures and Algorithms · Computer Science 2010-11-03 Andrej Bogdanov , Fan Li

Let $G$ be an $n$-node simple directed planar graph with nonnegative edge weights. We study the fundamental problems of computing (1) a global cut of $G$ with minimum weight and (2) a~cycle of $G$ with minimum weight. The best previously…

Data Structures and Algorithms · Computer Science 2017-03-24 Hung-Chun Liang , Hsueh-I Lu

We give a fully dynamic algorithm maintaining a $(1-\varepsilon)$-approximate directed densest subgraph in $\tilde{O}(\log^3(n)/\varepsilon^6)$ amortized time or $\tilde{O}(\log^4(n)/\varepsilon^7)$ worst-case time per edge update (where…

Data Structures and Algorithms · Computer Science 2023-12-19 Richard Li , Kent Quanrud

Reducing the running time of graph algorithms is vital for tackling real-world problems such as shortest paths and matching in large-scale graphs, where path information plays a crucial role. To address this critical challenge, this paper…

Data Structures and Algorithms · Computer Science 2026-04-14 Akshar Chavan , Sanaz Rabinia , Daniel Grosu , Marco Brocanelli

We study the problem of finding a small sparse cut in an undirected graph. Given an undirected graph G=(V,E) and a parameter k <= |E|, the small sparsest cut problem is to find a subset of vertices S with minimum conductance among all sets…

Data Structures and Algorithms · Computer Science 2012-04-23 Tsz Chiu Kwok , Lap Chi Lau

The problem of computing the vertex expansion of a graph is an NP-hard problem. The current best worst-case approximation guarantees for computing the vertex expansion of a graph are a $O(\sqrt{\log n})$-approximation algorithm due to…

Data Structures and Algorithms · Computer Science 2018-05-25 Anand Louis , Rakesh Venkat

The distributed single-source shortest paths problem is one of the most fundamental and central problems in the message-passing distributed computing. Classical Bellman-Ford algorithm solves it in $O(n)$ time, where $n$ is the number of…

Data Structures and Algorithms · Computer Science 2017-05-02 Michael Elkin

We present linear time {\it in-place} algorithms for several basic and fundamental graph problems including the well-known graph search methods (like depth-first search, breadth-first search, maximum cardinality search), connectivity…

Data Structures and Algorithms · Computer Science 2019-07-24 Sankardeep Chakraborty , Kunihiko Sadakane , Srinivasa Rao Satti

We introduce the notion of {\em fair cuts} as an approach to leverage approximate $(s,t)$-mincut (equivalently $(s,t)$-maxflow) algorithms in undirected graphs to obtain near-linear time approximation algorithms for several cut problems.…

Data Structures and Algorithms · Computer Science 2023-01-13 Jason Li , Danupon Nanongkai , Debmalya Panigrahi , Thatchaphol Saranurak

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

There is a huge difference in techniques and runtimes of distributed algorithms for problems that can be solved by a sequential greedy algorithm and those that cannot. A prime example of this contrast appears in the edge coloring problem:…

Data Structures and Algorithms · Computer Science 2025-05-27 Manuel Jakob , Yannic Maus , Florian Schager

Bipartite Correlation clustering is the problem of generating a set of disjoint bi-cliques on a set of nodes while minimizing the symmetric difference to a bipartite input graph. The number or size of the output clusters is not constrained…

Data Structures and Algorithms · Computer Science 2010-12-15 Nir Ailon , Noa Avigdor-Elgrabli , Edo Liberty