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Related papers: Eccentricity queries and beyond using Hub Labels

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We describe a way of assigning labels to the vertices of any undirected graph on up to $n$ vertices, each composed of $n/2+O(1)$ bits, such that given the labels of two vertices, and no other information regarding the graph, it is possible…

Data Structures and Algorithms · Computer Science 2014-04-15 Stephen Alstrup , Haim Kaplan , Mikkel Thorup , Uri Zwick

In this paper, we give a simple polynomial-time reduction of {L(p)-Labeling} on graphs with a small diameter to {Metric (Path) TSP}, which enables us to use numerous results on {(Metric) TSP}. On the practical side, we can utilize various…

Data Structures and Algorithms · Computer Science 2023-03-03 Tesshu Hanaka , Hirotaka Ono , Kosuke Sugiyama

We consider the Exact-Weight-H problem of finding a (not necessarily induced) subgraph H of weight 0 in an edge-weighted graph G. We show that for every H, the complexity of this problem is strongly related to that of the infamous k-Sum…

Data Structures and Algorithms · Computer Science 2013-04-30 Amir Abboud , Kevin Lewi

We study fundamental graph parameters such as the Diameter and Radius in directed graphs, when distances are measured using a somewhat unorthodox but natural measure: the distance between $u$ and $v$ is the minimum of the shortest path…

Data Structures and Algorithms · Computer Science 2019-06-18 Mina Dalirrooyfard , Virginia Vassilevska Williams , Nikhil Vyas , Nicole Wein , Yinzhan Xu , Yuancheng Yu

Given a vertex-labeled graph, each vertex $v$ is attached with a label from a set of labels. The vertex-label query desires the length of the shortest path from the given vertex to the set of vertices with the given label. We show how to…

Data Structures and Algorithms · Computer Science 2012-02-01 Mingfei Li , Christoffer Ma , Li Ning

Persistence diagrams (PDs) are now routinely used to summarize the underlying topology of complex data. Despite several appealing properties, incorporating PDs in learning pipelines can be challenging because their natural geometry is not…

Machine Learning · Statistics 2018-11-14 Théo Lacombe , Marco Cuturi , Steve Oudot

We give the first almost-linear time algorithm for computing the \emph{maximal $k$-edge-connected subgraphs} of an undirected unweighted graph for any constant $k$. More specifically, given an $n$-vertex $m$-edge graph $G=(V,E)$ and a…

Data Structures and Algorithms · Computer Science 2023-07-04 Thatchaphol Saranurak , Wuwei Yuan

Graph clustering aims to partition nodes into distinct clusters based on their similarity, thereby revealing relationships among nodes. Nevertheless, most existing methods do not fully utilize these edge weights. Leveraging edge weights in…

Machine Learning · Computer Science 2026-02-03 Haobing Liu , Yinuo Zhang , Tingting Wang , Ruobing Jiang , Yanwei Yu

In large networks, using the length of shortest paths as the distance measure has shortcomings. A well-studied shortcoming is that extending it to disconnected graphs and directed graphs is controversial. The second shortcoming is that a…

Data Structures and Algorithms · Computer Science 2018-04-03 Mostafa Haghir Chehreghani , Albert Bifet , Talel Abdessalem

Resistance distance computation is a fundamental problem in graph analysis, yet existing random walk-based methods are limited to approximate solutions and suffer from poor efficiency on small-treewidth graphs (e.g., road networks). In…

Databases · Computer Science 2025-09-08 Meihao Liao , Yueyang Pan , Rong-Hua Li , Guoren Wang

Finding the diameter of a graph in general cannot be done in truly subquadratic assuming the Strong Exponential Time Hypothesis (SETH), even when the underlying graph is unweighted and sparse. When restricting to concrete classes of graphs…

Data Structures and Algorithms · Computer Science 2024-11-01 Hsien-Chih Chang , Jie Gao , Hung Le

Proximity graph-based methods have emerged as a leading paradigm for approximate nearest neighbor (ANN) search in the system community. This paper presents fresh insights into the theoretical foundation of these methods. We describe an…

Data Structures and Algorithms · Computer Science 2025-09-10 Shangqi Lu , Yufei Tao

Visual rendering of graphs is a key task in the mapping of complex network data. Although most graph drawing algorithms emphasize aesthetic appeal, certain applications such as travel-time maps place more importance on visualization of…

Machine Learning · Statistics 2013-02-06 Brian Baingana , Georgios B. Giannakis

In this work we consider temporal graphs, i.e. graphs, each edge of which is assigned a set of discrete time-labels drawn from a set of integers. The labels of an edge indicate the discrete moments in time at which the edge is available. We…

Data Structures and Algorithms · Computer Science 2013-10-30 Paul G. Spirakis , Eleni Ch. Akrida

The eccentric connectivity index of a graph $G$ is $\xi^c(G) = \sum_{v \in V(G)}\varepsilon(v)\deg(v)$, and the eccentric distance sum is $\xi^d(G) = \sum_{v \in V(G)}\varepsilon(v)D(v)$, where $\varepsilon(v)$ is the eccentricity of $v$,…

Combinatorics · Mathematics 2020-05-07 Yaser Alizadeh , Sandi Klavžar

Consider an undirected weighted graph G=(V,E) with |V|=n and |E|=m, where each vertex v is assigned a label from a set L of \ell labels. We show how to construct a compact distance oracle that can answer queries of the form: "what is the…

Data Structures and Algorithms · Computer Science 2012-02-10 Shiri Chechik

Let $G$ be a connected finite graph with vertex set $V(G)$. The eccentricity $e(v)$ of a vertex $v$ is the distance from $v$ to a vertex farthest from $v$. The average eccentricity of $G$ is defined as $\frac{1}{|V(G)|}\sum_{v \in…

Combinatorics · Mathematics 2019-09-10 P. Dankelmann , F. J. Osaye

We study the succinct representations of vertex cuts by centralized oracles and labeling schemes. For an undirected $n$-vertex graph $G = (V,E)$ and integer parameter $f \geq 1$, the goal is supporting vertex cut queries: Given $F \subseteq…

Data Structures and Algorithms · Computer Science 2026-05-01 Yonggang Jiang , Merav Parter , Asaf Petruschka

Real-world vector embeddings are usually associated with extra labels, such as attributes and keywords. Many applications require the nearest neighbor search that contains specific labels, such as searching for product image embeddings…

Databases · Computer Science 2025-12-12 Mingyu Yang , Wenxuan Xia , Wentao Li , Raymond Chi-Wing Wong , Wei Wang

In this thesis I propose an algorithm to heuristically calculate different distance measures on uncertain graphs (i.e. graphs where edges only exist with a certain probability) and apply this to the heuristic calculation of harmonic…

Discrete Mathematics · Computer Science 2024-09-27 Daniel Ketels
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