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Boxicity of a graph G(V, E) is the minimum integer k such that G can be represented as the intersection graph of axis parallel boxes in $\mathbb{R}^k$. Cubicity is a variant of boxicity, where the axis parallel boxes in the intersection…

Discrete Mathematics · Computer Science 2015-06-09 Abhijin Adiga , Jasine Babu , L. Sunil Chandran

The index coding problem is concerned with broadcasting encoded information to a collection of receivers in a way that enables each receiver to discover its required data based on its side information, which comprises the data required by…

Data Structures and Algorithms · Computer Science 2024-08-19 Dror Chawin , Ishay Haviv

We give a new $(1+\epsilon)$-approximation for sparsest cut problem on graphs where small sets expand significantly more than the sparsest cut (sets of size $n/r$ expand by a factor $\sqrt{\log n\log r}$ bigger, for some small $r$; this…

Data Structures and Algorithms · Computer Science 2013-04-12 Sanjeev Arora , Rong Ge , Ali Kemal Sinop

We present the first work-optimal polylogarithmic-depth parallel algorithm for the minimum cut problem on non-sparse graphs. For $m\geq n^{1+\epsilon}$ for any constant $\epsilon>0$, our algorithm requires $O(m \log n)$ work and $O(\log^3…

Data Structures and Algorithms · Computer Science 2021-02-19 Andrés López-Martínez , Sagnik Mukhopadhyay , Danupon Nanongkai

In the minimum $k$-cut problem, we want to find the minimum number of edges whose deletion breaks the input graph into at least $k$ connected components. The classic algorithm of Karger and Stein runs in $\tilde O(n^{2k-2})$ time, and…

Data Structures and Algorithms · Computer Science 2021-12-02 Zhiyang He , Jason Li

In this short paper, we present an improved algorithm for approximating the minimum cut on distributed (CONGEST) networks. Let $\lambda$ be the minimum cut. Our algorithm can compute $\lambda$ exactly in…

Data Structures and Algorithms · Computer Science 2014-05-16 Danupon Nanongkai

We demonstrate that the best $k$-sparse approximation of a length-$n$ vector can be recovered within a $(1+\epsilon)$-factor approximation in $O((k/\epsilon) \log n)$ time using a non-adaptive linear sketch with $O((k/\epsilon) \log n)$…

Data Structures and Algorithms · Computer Science 2025-10-24 Nick Fischer , Vasileios Nakos

We consider the classical Minimum Crossing Number problem: given an $n$-vertex graph $G$, compute a drawing of $G$ in the plane, while minimizing the number of crossings between the images of its edges. This is a fundamental and extensively…

Data Structures and Algorithms · Computer Science 2022-02-15 Julia Chuzhoy , Zihan Tan

In this paper we provide a $\tilde{O}(m\sqrt{n})$ time algorithm that computes a $3$-multiplicative approximation of the girth of a $n$-node $m$-edge directed graph with non-negative edge lengths. This is the first algorithm which…

Data Structures and Algorithms · Computer Science 2020-04-15 Shiri Chechik , Yang P. Liu , Omer Rotem , Aaron Sidford

Dynamically maintaining the minimum cut in a graph $G$ under edge insertions and deletions is a fundamental problem in dynamic graph algorithms for which no conditional lower bound on the time per operation exists. In an $n$-node graph the…

Data Structures and Algorithms · Computer Science 2025-01-07 Antoine El-Hayek , Monika Henzinger , Jason Li

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

It is known that a better than $2$-approximation algorithm for the girth in dense directed unweighted graphs needs $n^{3-o(1)}$ time unless one uses fast matrix multiplication. Meanwhile, the best known approximation factor for a…

Data Structures and Algorithms · Computer Science 2020-04-28 Mina Dalirrooyfard , Virginia Vassilevska Williams

We propose an $O(\log n)$-approximation algorithm for the bipartiteness ratio of undirected graphs introduced by Trevisan (SIAM Journal on Computing, vol. 41, no. 6, 2012), where $n$ is the number of vertices. Our approach extends the…

Data Structures and Algorithms · Computer Science 2025-11-05 Tasuku Soma , Mingquan Ye , Yuichi Yoshida

We give O(log^2 n)-approximation algorithm based on the cut-matching framework of [10, 13, 14] for computing the sparsest cut on directed graphs. Our algorithm uses only O(log^2 n) single commodity max-flow computations and thus breaks the…

Data Structures and Algorithms · Computer Science 2015-03-17 Anand Louis

Graph-based nearest neighbor search methods have seen a surge of popularity in recent years, offering state-of-the-art performance across a wide variety of applications. Central to these methods is the task of constructing a sparse…

Data Structures and Algorithms · Computer Science 2025-10-24 Alex Conway , Laxman Dhulipala , Martin Farach-Colton , Rob Johnson , Ben Landrum , Christopher Musco , Yarin Shechter , Torsten Suel , Richard Wen

We introduce the $st$-cut version the Sparsest-Cut problem, where the goal is to find a cut of minimum sparsity among those separating two distinguished vertices $s,t\in V$. Clearly, this problem is at least as hard as the usual (non-$st$)…

Data Structures and Algorithms · Computer Science 2016-09-26 Robert Krauthgamer , Tal Wagner

This paper presents a linear FPT algorithm to find a tree decomposition with a 2-approximation of the treewidth with a significantly smaller exponential dependence on the treewidth. The algorithm runs in time $O(\text{poly}(k) 81^k n)$,…

Data Structures and Algorithms · Computer Science 2025-07-08 Mahdi Belbasi , Martin Fürer , Medha Kumar

The Max-Cut problem is known to be NP-hard on general graphs, while it can be solved in polynomial time on planar graphs. In this paper, we present a fixed-parameter tractable algorithm for the problem on `almost' planar graphs: Given an…

Data Structures and Algorithms · Computer Science 2019-05-27 Yasuaki Kobayashi , Yusuke Kobayashi , Shuichi Miyazaki , Suguru Tamaki

We give an algorithm that decides whether the bipartite crossing number of a given graph is at most $k$. The running time of the algorithm is upper bounded by $2^{O(k)} + n^{O(1)}$, where $n$ is the number of vertices of the input graph,…

Data Structures and Algorithms · Computer Science 2015-12-21 Yasuaki Kobayashi , Hisao Tamaki

We study the design of fixed-parameter algorithms for problems already known to be solvable in polynomial time. The main motivation is to get more efficient algorithms for problems with unattractive polynomial running times. Here, we focus…

Computational Complexity · Computer Science 2021-01-06 Archontia C. Giannopoulou , George B. Mertzios , Rolf Niedermeier