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We present a succinct data structure for permutation graphs, and their superclass of circular permutation graphs, i.e., data structures using optimal space up to lower order terms. Unlike concurrent work on circle graphs (Acan et al. 2022),…

Data Structures and Algorithms · Computer Science 2022-09-27 Konstantinos Tsakalidis , Sebastian Wild , Viktor Zamaraev

We consider distance queries in vertex-labeled planar graphs. For any fixed $0 < \epsilon \leq 1/2$ we show how to preprocess a directed planar graph with vertex labels and arc lengths into a data structure that answers queries of the…

Data Structures and Algorithms · Computer Science 2017-12-19 Shay Mozes , Eyal E. Skop

We consider the problem of privately answering queries defined on databases which are collections of points belonging to some metric space. We give simple, computationally efficient algorithms for answering distance queries defined over an…

Data Structures and Algorithms · Computer Science 2012-12-03 Zhiyi Huang , Aaron Roth

We consider the problem of designing a succinct data structure for {\it path graphs} (which are a proper subclass of chordal graphs and a proper superclass of interval graphs) on $n$ vertices while supporting degree, adjacency, and…

Data Structures and Algorithms · Computer Science 2023-03-03 Girish Balakrishnan , Sankardeep Chakraborty , N S Narayanaswamy , Kunihiko Sadakane

The Fr\'echet distance is a popular distance measure for curves which naturally lends itself to fundamental computational tasks, such as clustering, nearest-neighbor searching, and spherical range searching in the corresponding metric…

Computational Geometry · Computer Science 2018-08-07 Anne Driemel , Amer Krivošija

Many methods in differentially private model training rely on computing the similarity between a query point (such as public or synthetic data) and private data. We abstract out this common subroutine and study the following fundamental…

Cryptography and Security · Computer Science 2024-03-15 Arturs Backurs , Zinan Lin , Sepideh Mahabadi , Sandeep Silwal , Jakub Tarnawski

In distance query reconstruction, we wish to reconstruct the edge set of a hidden graph by asking as few distance queries as possible to an oracle. Given two vertices $u$ and $v$, the oracle returns the shortest path distance between $u$…

Data Structures and Algorithms · Computer Science 2024-10-17 Paul Bastide , Carla Groenland

We present a dual fault-tolerant distance oracle for undirected and unweighted graphs. Given a set $F$ of two edges, as well as a source node $s$ and a destination node $t$, our oracle returns the length of the shortest path from $s$ to $t$…

Data Structures and Algorithms · Computer Science 2024-07-03 Dipan Dey , Manoj Gupta

A suitable measure for the similarity of shapes represented by parameterized curves or surfaces is the Fr\'echet distance. Whereas efficient algorithms are known for computing the Fr\'echet distance of polygonal curves, the same problem for…

Computational Geometry · Computer Science 2007-05-23 Helmut Alt , Maike Buchin

In the sensitive distance oracle problem, there are three phases. We first preprocess a given directed graph $G$ with $n$ nodes and integer weights from $[-W,W]$. Second, given a single batch of $f$ edge insertions and deletions, we update…

Data Structures and Algorithms · Computer Science 2019-07-23 Jan van den Brand , Thatchaphol Saranurak

We develop data structures for dynamic closest pair problems with arbitrary distance functions, that do not necessarily come from any geometric structure on the objects. Based on a technique previously used by the author for Euclidean…

Data Structures and Algorithms · Computer Science 2010-01-21 David Eppstein

Since its introduction to computational geometry by Alt and Godau in 1992, the Fr\'echet distance has been a mainstay of algorithmic research on curve similarity computations. The focus of the research has been on comparing polygonal…

Computational Geometry · Computer Science 2024-01-09 Jacobus Conradi , Anne Driemel , Benedikt Kolbe

Subtrajectory clustering is an important variant of the trajectory clustering problem, where the start and endpoints of trajectory patterns within the collected trajectory data are not known in advance. We study this problem in the form of…

Computational Geometry · Computer Science 2022-04-22 Frederik Brüning , Jacobus Conradi , Anne Driemel

In this paper, we consider the following query problem: given two weighted point sets $A$ and $B$ in the Euclidean space $\mathbb{R}^d$, we want to quickly determine that whether their earth mover's distance (EMD) is larger or smaller than…

Computational Geometry · Computer Science 2020-06-16 Hu Ding , Tan Chen , Fan Yang , Mingyue Wang

In this paper we propose and study a new complexity model for approximation algorithms. The main motivation are practical problems over large data sets that need to be solved many times for different scenarios, e.g., many multicast trees…

Data Structures and Algorithms · Computer Science 2010-06-18 Marek Cygan , Lukasz Kowalik , Marcin Mucha , Marcin Pilipczuk , Piotr Sankowski

We consider preprocessing a set $S$ of $n$ points in convex position in the plane into a data structure supporting queries of the following form: given a point $q$ and a directed line $\ell$ in the plane, report the point of $S$ that is…

Computational Geometry · Computer Science 2017-10-16 Boris Aronov , Prosenjit Bose , Erik D. Demaine , Joachim Gudmundsson , John Iacono , Stefan Langerman , Michiel Smid

We revisit once more the problem of designing an oracle for answering connectivity queries in undirected graphs in the presence of vertex failures. Specifically, given an undirected graph $G$ with $n$ vertices and $m$ edges and an integer…

Data Structures and Algorithms · Computer Science 2023-09-06 Evangelos Kosinas

An $f$-edge fault-tolerant distance sensitive oracle ($f$-DSO) with stretch $\sigma \ge 1$ is a data structure that preprocesses a given undirected, unweighted graph $G$ with $n$ vertices and $m$ edges, and a positive integer $f$. When…

Data Structures and Algorithms · Computer Science 2024-08-07 Davide Bilò , Shiri Chechik , Keerti Choudhary , Sarel Cohen , Tobias Friedrich , Simon Krogmann , Martin Schirneck

We propose a novel method of introducing structure into existing machine learning techniques by developing structure-based similarity and distance measures. To learn structural information, low-dimensional structure of the data is captured…

Machine Learning · Statistics 2011-10-27 Joseph Wang , Venkatesh Saligrama , David A. Castañón

We consider the problem of building Distance Sensitivity Oracles (DSOs). Given a directed graph $G=(V, E)$ with edge weights in $\{1, 2, \dots, M\}$, we need to preprocess it into a data structure, and answer the following queries: given…

Data Structures and Algorithms · Computer Science 2021-09-03 Hanlin Ren
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