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We study the approximability of the maximum size independent set (MIS) problem in bounded degree graphs. This is one of the most classic and widely studied NP-hard optimization problems. We focus on the well known minimum degree greedy…

Data Structures and Algorithms · Computer Science 2020-02-03 Piotr Krysta , Mathieu Mari , Nan Zhi

A graph $G$ is called B$_k$-VPG (resp., B$_k$-EPG), for some constant $k\geq 0$, if it has a string representation on a grid such that each vertex is an orthogonal path with at most $k$ bends and two vertices are adjacent in $G$ if and only…

Computational Geometry · Computer Science 2017-02-21 Saeed Mehrabi

We contribute an approach to the problem of locally computing sparse connected subgraphs of dense graphs. In this setting, given an edge in a connected graph $G = (V, E)$, an algorithm locally decides its membership in a sparse connected…

Data Structures and Algorithms · Computer Science 2020-07-13 Rogers Epstein

We consider the problem of creating plane orthogonal drawings of 4-planar graphs (planar graphs with maximum degree 4) with constraints on the number of bends per edge. More precisely, we have a flexibility function assigning to each edge…

Data Structures and Algorithms · Computer Science 2015-01-08 Thomas Bläsius , Sebastian Lehmann , Ignaz Rutter

Our work concerns algorithms for an unweighted variant of Maximum Flow. In the All-Pairs Connectivity (APC) problem, we are given a graph $G$ on $n$ vertices and $m$ edges, and are tasked with computing the maximum number of edge-disjoint…

Data Structures and Algorithms · Computer Science 2023-05-04 Shyan Akmal , Ce Jin

Federated training methods have gained popularity for graph learning with applications including friendship graphs of social media sites and customer-merchant interaction graphs of huge online marketplaces. However, privacy regulations…

Machine Learning · Computer Science 2024-12-23 Siddharth Ambekar , Yuhang Yao , Ryan Li , Carlee Joe-Wong

We present fixed parameter tractable algorithms for the conflict-free coloring problem on graphs. Given a graph $G=(V,E)$, \emph{conflict-free coloring} of $G$ refers to coloring a subset of $V$ such that for every vertex $v$, there is a…

Data Structures and Algorithms · Computer Science 2019-05-07 Akanksha Agrawal , Pradeesha Ashok , Meghana M Reddy , Saket Saurabh , Dolly Yadav

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

The growing amount of applications that generate vast amount of data in short time scales render the problem of partial monitoring, coupled with prediction, a rather fundamental one. We study the aforementioned canonical problem under the…

Data Structures and Algorithms · Computer Science 2016-08-02 Michalis Kallitsis , Stilian Stoev , George Michailidis

Given a graph $G=(V,E)$, the problem of \gb{} is to find a sequence of nodes from $V$, called burning sequence, in order to burn the whole graph. This is a discrete-step process, in each step an unburned vertex is selected as an agent to…

Data Structures and Algorithms · Computer Science 2022-09-16 Rahul Kumar Gautam , Anjeneya Swami Kare , Durga Bhavani S

Graph partitioning is the problem of dividing the nodes of a graph into balanced partitions while minimizing the edge cut across the partitions. Due to its combinatorial nature, many approximate solutions have been developed, including…

Machine Learning · Computer Science 2019-03-05 Azade Nazi , Will Hang , Anna Goldie , Sujith Ravi , Azalia Mirhoseini

Graph alignment aims at finding the vertex correspondence between two correlated graphs, a task that frequently occurs in graph mining applications such as social network analysis. Attributed graph alignment is a variant of graph alignment,…

Data Structures and Algorithms · Computer Science 2024-03-13 Ziao Wang , Ning Zhang , Weina Wang , Lele Wang

We consider the graph $k$-partitioning problem under the min-max objective, termed as Minmax $k$-cut. The input here is a graph $G=(V,E)$ with non-negative edge weights $w:E\rightarrow \mathbb{R}_+$ and an integer $k\geq 2$ and the goal is…

Data Structures and Algorithms · Computer Science 2020-11-09 Karthekeyan Chandrasekaran , Weihang Wang

This paper considers a natural fault-tolerant shortest paths problem: for some constant integer $f$, given a directed weighted graph with no negative cycles and two fixed vertices $s$ and $t$, compute (either explicitly or implicitly) for…

Data Structures and Algorithms · Computer Science 2022-09-16 Virginia Vassilevska Williams , Eyob Woldeghebriel , Yinzhan Xu

Graphs are a natural representation of data from various contexts, such as social connections, the web, road networks, and many more. In the last decades, many of these networks have become enormous, requiring efficient algorithms to cut…

Data Structures and Algorithms · Computer Science 2021-08-11 Alexander Noe

In the $k$-connected directed Steiner tree problem ($k$-DST), we are given an $n$-vertex directed graph $G=(V,E)$ with edge costs, a connectivity requirement $k$, a root $r\in V$ and a set of terminals $T\subseteq V$. The goal is to find a…

Data Structures and Algorithms · Computer Science 2024-08-21 Chao Liao , Qingyun Chen , Bundit Laekhanukit , Yuhao Zhang

Many discrete optimization problems amount to selecting a feasible set of edges of least weight. We consider in this paper the context of spatial graphs where the positions of the vertices are uncertain and belong to known uncertainty sets.…

Data Structures and Algorithms · Computer Science 2022-09-27 Marin Bougeret , Jérémy Omer , Michael Poss

Given a $k$-vertex-connected graph $G$ and a set $S$ of extra edges (links), the goal of the $k$-vertex-connectivity augmentation problem is to find a set $S' \subseteq S$ of minimum size such that adding $S'$ to $G$ makes it…

Data Structures and Algorithms · Computer Science 2021-11-04 Waldo Gálvez , Francisco Sanhueza-Matamala , José A. Soto

We introduce a binary embedding framework, called Proximity Preserving Code (PPC), which learns similarity and dissimilarity between data points to create a compact and affinity-preserving binary code. This code can be used to apply fast…

Machine Learning · Computer Science 2020-02-06 Inbal Lav , Shai Avidan , Yoram Singer , Yacov Hel-Or

In the stochastic matching problem, we are given a general (not necessarily bipartite) graph $G(V,E)$, where each edge in $E$ is realized with some constant probability $p > 0$ and the goal is to compute a bounded-degree (bounded by a…

Data Structures and Algorithms · Computer Science 2017-05-08 Sepehr Assadi , Sanjeev Khanna , Yang Li