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Dynamic programming on various graph decompositions is one of the most fundamental techniques used in parameterized complexity. Unfortunately, even if we consider concepts as simple as path or tree decompositions, such dynamic programming…

A commonly used paradigm for representing graphs is to use a vector that contains normalized frequencies of occurrence of certain motifs or sub-graphs. This vector representation can be used in a variety of applications, such as, for…

Machine Learning · Computer Science 2014-03-05 Pinar Yanardag , S. V. N. Vishwanathan

Fully dynamic graph is a data structure that (1) supports edge insertions and deletions and (2) answers problem specific queries. The time complexity of (1) and (2) are referred to as the update time and the query time respectively. There…

Data Structures and Algorithms · Computer Science 2014-04-30 Yoichi Iwata , Keigo Oka

Identifying the connected components of a graph, apart from being a fundamental problem with countless applications, is a key primitive for many other algorithms. In this paper, we consider this problem in parallel settings. Particularly,…

Data Structures and Algorithms · Computer Science 2020-03-13 Soheil Behnezhad , Laxman Dhulipala , Hossein Esfandiari , Jakub Łącki , Vahab Mirrokni

The Sparsest Cut is a fundamental optimization problem that has been extensively studied. For planar inputs the problem is in $P$ and can be solved in $\tilde{O}(n^3)$ time if all vertex weights are $1$. Despite a significant amount of…

Data Structures and Algorithms · Computer Science 2020-07-07 Amir Abboud , Vincent Cohen-Addad , Philip N. Klein

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

Sampling of signals defined over the nodes of a graph is one of the crucial problems in graph signal processing. While in classical signal processing sampling is a well defined operation, when we consider a graph signal many new challenges…

Information Theory · Computer Science 2019-05-30 Diego Valsesia , Giulia Fracastoro , Enrico Magli

We study the problem of computing an approximate maximum cardinality matching in the semi-streaming model when edges arrive in a \emph{random} order. In the semi-streaming model, the edges of the input graph G = (V,E) are given as a stream…

Data Structures and Algorithms · Computer Science 2020-05-04 Aaron Bernstein

We initiate the algorithmic study of retracting a graph into a cycle in the graph, which seeks a mapping of the graph vertices to the cycle vertices, so as to minimize the maximum stretch of any edge, subject to the constraint that the…

Data Structures and Algorithms · Computer Science 2019-04-29 Samuel Haney , Mehraneh Liaee , Bruce M. Maggs , Debmalya Panigrahi , Rajmohan Rajaraman , Ravi Sundaram

We give fast, simple, and implementable catalytic logspace algorithms for two fundamental graph problems. First, a randomized catalytic algorithm for $s\to t$ connectivity running in $\widetilde{O}(nm)$ time, and a deterministic catalytic…

Data Structures and Algorithms · Computer Science 2025-09-09 James Cook , Edward Pyne

Graph reconstruction can efficiently detect the underlying topology of massive networks such as the Internet. Given a query oracle and a set of nodes, the goal is to obtain the edge set by performing as few queries as possible. An algorithm…

Data Structures and Algorithms · Computer Science 2024-07-29 Clara Stegehuis , Lotte Weedage

Given a source of iid samples of edges of an input graph $G$ with $n$ vertices and $m$ edges, how many samples does one need to compute a constant factor approximation to the maximum matching size in $G$? Moreover, is it possible to obtain…

Data Structures and Algorithms · Computer Science 2019-07-15 Michael Kapralov , Slobodan Mitrović , Ashkan Norouzi-Fard , Jakab Tardos

We consider the problem of estimating the value of max cut in a graph in the streaming model of computation. At one extreme, there is a trivial $2$-approximation for this problem that uses only $O(\log n)$ space, namely, count the number of…

Data Structures and Algorithms · Computer Science 2014-09-09 Michael Kapralov , Sanjeev Khanna , Madhu Sudan

We give an algorithm for finding the arboricity of a weighted, undirected graph, defined as the minimum number of spanning forests that cover all edges of the graph, in $\sqrt{n} m^{1+o(1)}$ time. This improves on the previous best bound of…

Data Structures and Algorithms · Computer Science 2025-07-22 Ruoxu Cen , Henry Fleischmann , George Z. Li , Jason Li , Debmalya Panigrahi

In this paper we give the first efficient algorithms for the $k$-center problem on dynamic graphs undergoing edge updates. In this problem, the goal is to partition the input into $k$ sets by choosing $k$ centers such that the maximum…

Data Structures and Algorithms · Computer Science 2024-01-10 Emilio Cruciani , Sebastian Forster , Gramoz Goranci , Yasamin Nazari , Antonis Skarlatos

We consider the (exact, minimum) $k$-cut problem: given a graph and an integer $k$, delete a minimum-weight set of edges so that the remaining graph has at least $k$ connected components. This problem is a natural generalization of the…

Data Structures and Algorithms · Computer Science 2019-10-08 Jason Li

In this paper we present improved bounds for approximating maximum matchings in bipartite graphs in the streaming model. First, we consider the question of how well maximum matching can be approximated in a single pass over the input using…

Data Structures and Algorithms · Computer Science 2021-03-18 Michael Kapralov

One of the simplest problems on directed graphs is that of identifying the set of vertices reachable from a designated source vertex. This problem can be solved easily sequentially by performing a graph search, but efficient parallel…

Data Structures and Algorithms · Computer Science 2017-11-07 Jeremy T. Fineman

We initiate the investigation of the parameterized complexity of Diameter and Connectivity in the streaming paradigm. On the positive end, we show that knowing a vertex cover of size $k$ allows for algorithms in the Adjacency List (AL)…

Data Structures and Algorithms · Computer Science 2024-07-19 Jelle J. Oostveen , Erik Jan van Leeuwen

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
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