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Let $T=t_0 ... t_{n-1}$ be a text and $P = p_0 ... p_{m-1}$ a pattern taken from some finite alphabet set $\Sigma$, and let $\dist$ be a metric on $\Sigma$. We consider the problem of calculating the sum of distances between the symbols of…

Data Structures and Algorithms · Computer Science 2008-02-12 Klim Efremenko , Ely Porat

The Fr\'echet distance provides a natural and intuitive measure for the popular task of computing the similarity of two (polygonal) curves. While a simple algorithm computes it in near-quadratic time, a strongly subquadratic algorithm…

Computational Geometry · Computer Science 2019-01-08 Karl Bringmann , Marvin Künnemann , André Nusser

In this paper, we present a linear-time approximation scheme for $k$-means clustering of \emph{incomplete} data points in $d$-dimensional Euclidean space. An \emph{incomplete} data point with $\Delta>0$ unspecified entries is represented as…

Computational Geometry · Computer Science 2021-06-29 Kyungjin Cho , Eunjin Oh

Least squares approximation is a technique to find an approximate solution to a system of linear equations that has no exact solution. In a typical setting, one lets $n$ be the number of constraints and $d$ be the number of variables, with…

Data Structures and Algorithms · Computer Science 2010-09-28 Petros Drineas , Michael W. Mahoney , S. Muthukrishnan , Tamas Sarlos

The Fr\'echet distance is a computational mainstay for comparing polygonal curves. The Fr\'echet distance under translation, which is a translation invariant version, considers the similarity of two curves independent of their location in…

Computational Geometry · Computer Science 2025-01-23 Lotte Blank , Jacobus Conradi , Anne Driemel , Benedikt Kolbe , André Nusser , Marena Richter

The Earth Mover's Distance (EMD) is a state-of-the art metric for comparing discrete probability distributions, but its high distinguishability comes at a high cost in computational complexity. Even though linear-complexity approximation…

Machine Learning · Computer Science 2019-05-29 Kubilay Atasu , Thomas Mittelholzer

The distance transform algorithm is popular in computer vision and machine learning domains. It is used to minimize quadratic functions over a grid of points. Felzenszwalb and Huttenlocher (2004) describe an O(N) algorithm for computing the…

Computational Geometry · Computer Science 2019-08-06 Mihir Sahasrabudhe , Siddhartha Chandra

Let $\tau$ and $\sigma$ be two polygonal curves in $\mathbb{R}^d$ for any fixed $d$. Suppose that $\tau$ and $\sigma$ have $n$ and $m$ vertices, respectively, and $m\le n$. While conditional lower bounds prevent approximating the Fr\'echet…

Computational Geometry · Computer Science 2025-03-18 Siu-Wing Cheng , Haoqiang Huang , Shuo Zhang

We study the computation of the diameter and radius under the rectilinear link distance within a rectilinear polygonal domain of $n$ vertices and $h$ holes. We introduce a \emph{graph of oriented distances} to encode the distance between…

Consider a set $P$ of $n$ points in $\mathbb{R}^d$. In the discrete median line segment problem, the objective is to find a line segment bounded by a pair of points in $P$ such that the sum of the Euclidean distances from $P$ to the line…

Computational Geometry · Computer Science 2022-02-16 Ovidiu Daescu , Ka Yaw Teo

We consider approximate distance oracles for edge-weighted n-vertex undirected planar graphs. Given fixed epsilon > 0, we present a (1+epsilon)-approximate distance oracle with O(n(loglog n)^2) space and O((loglog n)^3) query time. This…

Data Structures and Algorithms · Computer Science 2016-01-06 Christian Wulff-Nilsen

The Fr\'{e}chet distance is a well-studied similarity measure between curves that is widely used throughout computer science. Motivated by applications where curves stem from paths and walks on an underlying graph (such as a road network),…

Computational Geometry · Computer Science 2024-11-20 Anne Driemel , Ivor van der Hoog , Eva Rotenberg

We study aspects of the Wasserstein distance in the context of self-similar measures. Computing this distance between two measures involves minimising certain moment integrals over the space of \emph{couplings}, which are measures on the…

Functional Analysis · Mathematics 2016-06-07 Jonathan M. Fraser

We study edit distance computation with preprocessing: the preprocessing algorithm acts on each string separately, and then the query algorithm takes as input the two preprocessed strings. This model is inspired by scenarios where we would…

Data Structures and Algorithms · Computer Science 2021-08-23 Elazar Goldenberg , Aviad Rubinstein , Barna Saha

Earth Mover's Distance (EMD) is an important similarity measure between two distributions, used in computer vision and many other application domains. However, its exact calculation is computationally and memory intensive, which hinders its…

Computer Vision and Pattern Recognition · Computer Science 2025-05-15 Guangyu Meng , Ruyu Zhou , Liu Liu , Peixian Liang , Fang Liu , Danny Chen , Michael Niemier , X. Sharon Hu

Similar subtrajectory search is a finer-grained operator that can better capture the similarities between one query trajectory and a portion of a data trajectory than the traditional similar trajectory search, which requires the two checked…

Databases · Computer Science 2023-08-09 Jiabao Jin , Peng Cheng , Lei Chen , Xuemin Lin , Wenjie Zhang

The Fr\'echet distance is a popular similarity measure that is well-understood for polygonal curves in $\mathbb{R}^d$: near-quadratic time algorithms exist, and conditional lower bounds suggest that these results cannot be improved…

Computational Geometry · Computer Science 2025-05-09 Thijs van der Horst , Marc van Kreveld , Tim Ophelders , Bettina Speckmann

A $(1+\epsilon)$-approximate distance oracle of an edge-weighted graph is a data structure that returns an approximate shortest path distance between any two query vertices up to a $(1+\epsilon)$ factor. Thorup (FOCS 2001, JACM 2004) and…

Data Structures and Algorithms · Computer Science 2021-11-08 Hung Le , Christian Wulff-Nilsen

We study the fundamental problem of approximating the edit distance of two strings. After an extensive line of research led to the development of a constant-factor approximation algorithm in almost-linear time, recent years have witnessed a…

Data Structures and Algorithms · Computer Science 2023-12-05 Karl Bringmann , Alejandro Cassis , Nick Fischer , Tomasz Kociumaka

Recent years have witnessed a tremendous growth using topological summaries, especially the persistence diagrams (encoding the so-called persistent homology) for analyzing complex shapes. Intuitively, persistent homology maps a potentially…

Computational Geometry · Computer Science 2021-04-19 Samantha Chen , Yusu Wang