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Modern graph or network datasets often contain rich structure that goes beyond simple pairwise connections between nodes. This calls for complex representations that can capture, for instance, edges of different types as well as so-called…

Social and Information Networks · Computer Science 2020-02-19 Ilya Amburg , Nate Veldt , Austin R. Benson

Point feature map labeling is a geometric problem, in which a set of input points must be labeled with a set of disjoint rectangles (the bounding boxes of the label texts). Typically, labeling models either use internal labels, which must…

Computational Geometry · Computer Science 2015-01-28 Maarten Löffler , Martin Nöllenburg , Frank Staals

The average distance from a node to all other nodes in a graph, or from a query point in a metric space to a set of points, is a fundamental quantity in data analysis. The inverse of the average distance, known as the (classic) closeness…

Social and Information Networks · Computer Science 2015-06-29 Shiri Chechik , Edith Cohen , Haim Kaplan

The task of node classification is to infer unknown node labels, given the labels for some of the nodes along with the network structure and other node attributes. Typically, approaches for this task assume homophily, whereby neighboring…

Social and Information Networks · Computer Science 2021-09-15 Arpit Merchant , Michael Mathioudakis

A distance oracle is a compact representation of the shortest distance matrix of a graph. It can be queried to approximate shortest paths between any pair of vertices. Any distance oracle that returns paths of worst-case stretch (2k-1) must…

Data Structures and Algorithms · Computer Science 2012-01-16 Rachit Agarwal , P. Brighten Godfrey , Sariel Har-Peled

An unweighted, undirected graph $G$ on $n$ nodes is said to have \emph{bandwidth} at most $k$ if its nodes can be labelled from $0$ to $n - 1$ such that no two adjacent nodes have labels that differ by more than $k$. It is known that one…

Data Structures and Algorithms · Computer Science 2026-02-03 Luis M. B. Varona

Classification is a major tool of statistics and machine learning. A classification method first processes a training set of objects with given classes (labels), with the goal of afterward assigning new objects to one of these classes. When…

Machine Learning · Statistics 2024-07-08 Jakob Raymaekers , Peter J. Rousseeuw , Mia Hubert

Due to their capacity to encode rich structural information, labeled graphs are often used for modeling various kinds of objects such as images, molecules, and chemical compounds. If pattern recognition problems such as clustering and…

Data Structures and Algorithms · Computer Science 2019-08-02 David B. Blumenthal

We consider the standard message passing model; we assume the system is fully synchronous: all processes start at the same time and time proceeds in synchronised rounds. In each round each vertex can transmit a different message of size…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-07-14 Y. Métivier , J. M. Robson , A. Zemmari

A temporal graph is a graph in which edges are assigned a time label. Two nodes u and v of a temporal graph are connected one to the other if there exists a path from u to v with increasing edge time labels. We consider the problem of…

Data Structures and Algorithms · Computer Science 2023-04-04 Alkida Balliu , Filippo Brunelli , Pierluigi Crescenzi , Dennis Olivetti , Laurent Viennot

A* is a classic and popular method for graphs search and path finding. It assumes the existence of a heuristic function $h(u,t)$ that estimates the shortest distance from any input node $u$ to the destination $t$. Traditionally, heuristics…

Computational Geometry · Computer Science 2021-11-22 Talya Eden , Piotr Indyk , Haike Xu

Given an unlabeled road map, we consider, from an algorithmic perspective, the cartographic problem to place non-overlapping road labels embedded in their roads. We first decompose the road network into logically coherent road sections,…

Computational Geometry · Computer Science 2016-05-16 Benjamin Niedermann , Martin Nöllenburg

Unravelling hidden patterns in datasets is a classical problem with many potential applications. In this paper, we present a challenge whose objective is to discover nonlinear relationships in noisy cloud of points. If a set of point…

Machine Learning · Statistics 2018-05-31 Terry Lyons , Imanol Perez Arribas

Graph Neural Networks (GNNs) have emerged as a powerful tool for semi-supervised node classification tasks. However, recent studies have revealed various biases in GNNs stemming from both node features and graph topology. In this work, we…

Machine Learning · Computer Science 2023-05-26 Haoyu Han , Xiaorui Liu , Feng Shi , MohamadAli Torkamani , Charu C. Aggarwal , Jiliang Tang

Distance-based unsupervised text classification is a method within text classification that leverages the semantic similarity between a label and a text to determine label relevance. This method provides numerous benefits, including fast…

Computation and Language · Computer Science 2025-10-14 Jens Van Nooten , Andriy Kosar , Guy De Pauw , Walter Daelemans

A graph $G$ is said to be $d$-distinguishable if there is a labeling of the vertices with $d$ labels so that only the trivial automorphism preserves the labels. The smallest such $d$ is the distinguishing number, Dist($G$). A subset of…

Combinatorics · Mathematics 2024-06-13 Debra Boutin , Sally Cockburn

This study poses the feature correspondence problem as a hypergraph node labeling problem. Candidate feature matches and their subsets (usually of size larger than two) are considered to be the nodes and hyperedges of a hypergraph. A…

Computer Vision and Pattern Recognition · Computer Science 2011-07-14 Toufiq Parag , Vladimir Pavlovic , Ahmed Elgammal

We describe a linear-time algorithm that finds a planar drawing of every graph of a simple line or pseudoline arrangement within a grid of area O(n^{7/6}). No known input causes our algorithm to use area \Omega(n^{1+\epsilon}) for any…

Computational Geometry · Computer Science 2015-07-16 David Eppstein

Labeling schemes are a prevalent paradigm in various computing settings. In such schemes, an oracle is given an input graph and produces a label for each of its nodes, enabling the labels to be used for various tasks. Fundamental examples…

Data Structures and Algorithms · Computer Science 2024-12-03 Keren Censor-Hillel , Einav Huberman

Given a graph $G$ and a set of terminals $T$, a \emph{distance emulator} of $G$ is another graph $H$ (not necessarily a subgraph of $G$) containing $T$, such that all the pairwise distances in $G$ between vertices of $T$ are preserved in…

Data Structures and Algorithms · Computer Science 2018-07-05 Hsien-Chih Chang , Paweł Gawrychowski , Shay Mozes , Oren Weimann
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