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In this paper we present an algorithmic framework for solving a class of combinatorial optimization problems on graphs with bounded pathwidth. The problems are NP-hard in general, but solvable in linear time on this type of graphs. The…

Data Structures and Algorithms · Computer Science 2012-12-18 Mugurel Ionut Andreica

We introduce a new technique for designing fixed-parameter algorithms for cut problems, namely randomized contractions. We apply our framework to obtain the first FPT algorithm for the Unique Label Cover problem and new FPT algorithms with…

Data Structures and Algorithms · Computer Science 2016-07-20 Rajesh Chitnis , Marek Cygan , MohammadTaghi Hajiaghayi , Marcin Pilipczuk , Michał Pilipczuk

Weighted counting problems are a natural generalization of counting problems where a weight is associated with every computational path of polynomial-time non-deterministic Turing machines and the goal is to compute the sum of the weights…

Computational Complexity · Computer Science 2019-01-11 Cassio P. de Campos , Georgios Stamoulis , Dennis Weyland

We study the problem of estimating the number of triangles in a graph stream. No streaming algorithm can get sublinear space on all graphs, so methods in this area bound the space in terms of parameters of the input graph such as the…

Data Structures and Algorithms · Computer Science 2019-04-18 John Kallaugher , Eric Price

Pattern counting in graphs is fundamental to network science tasks, and there are many scalable methods for approximating counts of small patterns, often called motifs, in large graphs. However, modern graph datasets now contain richer…

Social and Information Networks · Computer Science 2018-10-03 Paul Liu , Austin Benson , Moses Charikar

We present a new random sampling strategy for k-bandlimited signals defined on graphs, based on determinantal point processes (DPP). For small graphs, ie, in cases where the spectrum of the graph is accessible, we exhibit a DPP sampling…

Machine Learning · Computer Science 2017-03-07 Nicolas Tremblay , Pierre-Olivier Amblard , Simon Barthelmé

Graph sampling is a technique to pick a subset of vertices and/ or edges from original graph. Among various graph sampling approaches, Traversal Based Sampling (TBS) are widely used due to low cost and feasibility for many cases, in which…

Social and Information Networks · Computer Science 2022-09-28 Xiao Qi

An edge cover of a graph is a set of edges such that every vertex has at least an adjacent edge in it. Previously, approximation algorithm for counting edge covers is only known for 3 regular graphs and it is randomized. We design a very…

Data Structures and Algorithms · Computer Science 2014-11-04 Chengyu Lin , Jingcheng Liu , Pinyan Lu

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

As networks continue to increase in size, current methods must be capable of handling large numbers of nodes and edges in order to be practically relevant. Instead of working directly with the entire (large) network, analyzing sub-networks…

Social and Information Networks · Computer Science 2025-04-03 Eric Yanchenko

The paper presents fault-tolerant (FT) labeling schemes for general graphs, as well as, improved FT routing schemes. For a given $n$-vertex graph $G$ and a bound $f$ on the number of faults, an $f$-FT connectivity labeling scheme is a…

Data Structures and Algorithms · Computer Science 2021-06-02 Michal Dory , Merav Parter

We consider the problem of counting, in a given graph, the number of induced k-vertex subgraphs which have an even number of edges, and also the complementary problem of counting the k-vertex induced subgraphs having an odd number of edges.…

Combinatorics · Mathematics 2015-10-07 Mark Jerrum , Kitty Meeks

We revisit the problem of counting the number of copies of a fixed graph in a random graph or multigraph, including the case of constrained degrees. Our approach relies heavily on analytic combinatorics and on the notion of patchwork to…

Sampling random graphs with given properties is a key step in the analysis of networks, as random ensembles represent basic null models required to identify patterns such as communities and motifs. An important requirement is that the…

Methodology · Statistics 2015-02-23 Tiziano Squartini , Rossana Mastrandrea , Diego Garlaschelli

We study the parameterized complexity of the graph isomorphism problem when parameterized by width parameters related to tree decompositions. We apply the following technique to obtain fixed-parameter tractability for such parameters. We…

Discrete Mathematics · Computer Science 2014-03-31 Yota Otachi , Pascal Schweitzer

The use of random sampling in decision-making and control has become popular with the ease of access to graphic processing units that can generate and calculate multiple random trajectories for real-time robotic applications. In contrast to…

Robotics · Computer Science 2022-03-21 Hyung-Jin Yoon , Chuyuan Tao , Hunmin Kim , Naira Hovakimyan , Petros Voulgaris

An important tool in analyzing complex social and information networks is s-t simple path counting, which is known to be #P-complete. In this paper, we study efficient s-t simple path counting in directed graphs. For a given pair of…

Social and Information Networks · Computer Science 2022-07-01 Mostafa Haghir Chehreghani

We initiate the study of deterministic distributed graph algorithms with predictions in synchronous message passing systems. The process at each node in the graph is given a prediction, which is some extra information about the problem…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-01-01 Joan Boyar , Faith Ellen , Kim S. Larsen

Combining the techniques of approximation algorithms and parameterized complexity has long been considered a promising research area, but relatively few results are currently known. In this paper we study the parameterized approximability…

Data Structures and Algorithms · Computer Science 2014-02-18 Michael Lampis

We study the following problem: given an integer $k \ge 3$ and a simple graph $G$, sample a connected induced $k$-node subgraph of $G$ uniformly at random. This is a fundamental graph mining primitive with applications in social network…

Data Structures and Algorithms · Computer Science 2021-10-29 Marco Bressan