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We revisit a fundamental problem in string matching: given a pattern of length m and a text of length n, both over an alphabet of size $\sigma$, compute the Hamming distance between the pattern and the text at every location. Several…

Data Structures and Algorithms · Computer Science 2020-01-03 Timothy M. Chan , Shay Golan , Tomasz Kociumaka , Tsvi Kopelowitz , Ely Porat

Finding an exact maximum distance of two points in the given set is a fundamental computational problem which is solved in many applications. This paper presents a fast, simple to implement and robust algorithm for finding this maximum…

Data Structures and Algorithms · Computer Science 2017-08-10 Vaclav Skala , Zuzana Majdisova

Fr\'echet regression extends the principles of linear regression to accommodate responses valued in generic metric spaces. While this approach has primarily focused on exploring relationships between Euclidean predictors and non-Euclidean…

Statistics Theory · Mathematics 2026-02-25 Chang Jun Im , Jeong Min Jeon

We study subtrajectory clustering under the Fr\'echet distance. Given one or more trajectories, the task is to split the trajectories into several parts, such that the parts have a good clustering structure. We approach this problem via a…

Computational Geometry · Computer Science 2021-12-23 Hugo A. Akitaya , Frederik Brüning , Erin Chambers , Anne Driemel

We consider variants of the classical Frank-Wolfe algorithm for constrained smooth convex minimization, that instead of access to the standard oracle for minimizing a linear function over the feasible set, have access to an oracle that can…

Optimization and Control · Mathematics 2022-02-10 Dan Garber , Noam Wolf

Reconstructing a signal from squared linear (rank-one quadratic) measurements is a challenging problem with important applications in optics and imaging, where it is known as phase retrieval. This paper proposes two new phase retrieval…

Information Theory · Computer Science 2016-09-21 Cheng Qian , Nicholas D. Sidiropoulos , Kejun Huang , Lei Huang , H. C. So

We provide the first known algorithm that provably achieves $\varepsilon$-optimality within $\widetilde{\mathcal{O}}(1/\varepsilon)$ function evaluations for the discounted discrete-time LQR problem with unknown parameters, without relying…

Systems and Control · Electrical Eng. & Systems 2025-06-18 Amirreza Neshaei Moghaddam , Alex Olshevsky , Bahman Gharesifard

In this paper, we present a novel two-stage metric learning algorithm. We first map each learning instance to a probability distribution by computing its similarities to a set of fixed anchor points. Then, we define the distance in the…

Machine Learning · Computer Science 2014-05-16 Jun Wang , Ke Sun , Fei Sha , Stephane Marchand-Maillet , Alexandros Kalousis

In this paper, we propose new techniques for solving geometric optimization problems involving interpoint distances of a point set in the plane. Given a set $P$ of $n$ points in the plane and an integer $1 \leq k \leq \binom{n}{2}$, the…

Computational Geometry · Computer Science 2024-03-08 Haitao Wang , Yiming Zhao

We show that the Fr\'echet distance of two-dimensional parametrised surfaces in a metric space is computable in the bit-model of real computation. An analogous result in the real RAM model for piecewise-linear surfaces has recently been…

Computational Geometry · Computer Science 2018-04-04 Eike Neumann

In the classic polyline simplification problem we want to replace a given polygonal curve $P$, consisting of $n$ vertices, by a subsequence $P'$ of $k$ vertices from $P$ such that the polygonal curves $P$ and $P'$ are as close as possible.…

Computational Geometry · Computer Science 2025-09-15 Karl Bringmann , Bhaskar Ray Chaudhury

Lagrangian coherent structures (LCS) in fluid flows appear as co-dimension one ridges of the finite time Lyapunov exponent (FTLE) field. In three- dimensions this means two-dimensional ridges. A fast algorithm is presented here to locate…

Fluid Dynamics · Physics 2012-02-24 Doug Lipinski , Kamran Mohseni

Several researchers proposed using non-Euclidean metrics on point sets in Euclidean space for clustering noisy data. Almost always, a distance function is desired that recognizes the closeness of the points in the same cluster, even if the…

Computational Geometry · Computer Science 2015-03-02 Michael B. Cohen , Brittany Terese Fasy , Gary L. Miller , Amir Nayyeri , Donald R. Sheehy , Ameya Velingker

Distance covariance and distance correlation have been widely adopted in measuring dependence of a pair of random variables or random vectors. If the computation of distance covariance and distance correlation is implemented directly…

Computation · Statistics 2014-10-07 Xiaoming Huo , Gabor J. Szekely

We analyze the touring regions problem: find a ($1+\epsilon$)-approximate Euclidean shortest path in $d$-dimensional space that starts at a given starting point, ends at a given ending point, and visits given regions $R_1, R_2, R_3, \dots,…

Computational Geometry · Computer Science 2023-03-15 Benjamin Qi , Richard Qi , Xinyang Chen

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 propose a new $(1+O(\varepsilon))$-approximation algorithm with $O(n+ 1/\varepsilon^{\frac{(d-1)}{2}})$ running time for computing the diameter of a set of $n$ points in the $d$-dimensional Euclidean space for a fixed dimension $d$,…

Computational Geometry · Computer Science 2020-11-11 Mahdi Imanparast , Seyed Naser Hashemi

Let $P$ be a polygonal curve in $\mathbb{R}^D$ of length $n$, and $S$ be a point set of size $k$. The Curve/Point Set Matching problem consists of finding a polygonal curve $Q$ on $S$ such that its Fr\'echet distance from $P$ is less than a…

Computational Geometry · Computer Science 2014-05-06 Paul Accisano , Alper Üngör

Modern tracking technology has made the collection of large numbers of densely sampled trajectories of moving objects widely available. We consider a fundamental problem encountered when analysing such data: Given $n$ polygonal curves $S$…

Computational Geometry · Computer Science 2017-07-18 Peyman Afshani , Anne Driemel

In 2015, Driemel, Krivo\v{s}ija and Sohler introduced the $(k,\ell)$-median problem for clustering polygonal curves under the Fr\'echet distance. Given a set of input curves, the problem asks to find $k$ median curves of at most $\ell$…

Computational Geometry · Computer Science 2020-11-04 Maike Buchin , Anne Driemel , Dennis Rohde
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