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The Earth Mover's Distance (EMD) computes the optimal cost of transforming one distribution into another, given a known transport metric between them. In deep learning, the EMD loss allows us to embed information during training about the…

Computer Vision and Pattern Recognition · Computer Science 2016-11-24 Manuel Martinez , Monica Haurilet , Ziad Al-Halah , Makarand Tapaswi , Rainer Stiefelhagen

The edit distance between two strings is defined as the smallest number of insertions, deletions, and substitutions that need to be made to transform one of the strings to another one. Approximating edit distance in subquadratic time is…

Data Structures and Algorithms · Computer Science 2018-04-27 Mahdi Boroujeni , Soheil Ehsani , Mohammad Ghodsi , MohammadTaghi HajiAghayi , Saeed Seddighin

The matching distance is a computationally tractable topological measure to compare multi-filtered simplicial complexes. We design efficient algorithms for approximating the matching distance of two bi-filtered complexes to any desired…

Computational Geometry · Computer Science 2020-04-02 Michael Kerber , Arnur Nigmetov

Optimal transport (OT) distances between probability distributions are parameterized by the ground metric they use between observations. Their relevance for real-life applications strongly hinges on whether that ground metric parameter is…

Machine Learning · Statistics 2020-11-06 Matthieu Heitz , Nicolas Bonneel , David Coeurjolly , Marco Cuturi , Gabriel Peyré

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

We consider the problem of finding an optimal transport plan between an absolutely continuous measure $\mu$ on $\mathcal{X} \subset \mathbb{R}^d$ and a finitely supported measure $\nu$ on $\mathbb{R}^d$ when the transport cost is the…

Numerical Analysis · Mathematics 2018-10-08 Valentin Hartmann , Dominic Schuhmacher

It is an open question whether there exists a polynomial-time algorithm for computing the rotation distances between pairs of extended ordered binary trees. The problem of computing the rotation distance between an arbitrary pair of trees,…

Data Structures and Algorithms · Computer Science 2020-01-20 Sean Cleary , Roland Maio

The quartet distance is a measure of similarity used to compare two unrooted phylogenetic trees on the same set of $n$ leaves, defined as the number of subsets of four leaves related by a different topology in both trees. After a series of…

Data Structures and Algorithms · Computer Science 2020-12-03 Bartłomiej Dudek , Paweł Gawrychowski

The tree edit distance is a natural dissimilarity measure between rooted ordered trees whose nodes are labeled over an alphabet $\Sigma$. It is defined as the minimum number of node edits (insertions, deletions, and relabelings) required to…

Data Structures and Algorithms · Computer Science 2025-07-04 Tomasz Kociumaka , Ali Shahali

Let $(\{1,2,\ldots,n\},d)$ be a metric space. We analyze the expected value and the variance of $\sum_{i=1}^{\lfloor n/2\rfloor}\,d({\boldsymbol{\pi}}(2i-1),{\boldsymbol{\pi}}(2i))$ for a uniformly random permutation ${\boldsymbol{\pi}}$ of…

Data Structures and Algorithms · Computer Science 2017-03-27 Ching-Lueh Chang

We study the minimum diameter problem for a set of inexact points. By inexact, we mean that the precise location of the points is not known. Instead, the location of each point is restricted to a contineus region ($\impre$ model) or a…

Computational Geometry · Computer Science 2017-04-03 Mohammad Ghodsi , Hamid Homapour , Masoud Seddighin

Given $n$ points in a circular region $C$ in the plane, we study the problems of moving the $n$ points to its boundary to form a regular $n$-gon such that the maximum (min-max) or the sum (min-sum) of the Euclidean distances traveled by the…

Computational Geometry · Computer Science 2011-07-07 Danny Z. Chen , Xuehou Tan , Haitao Wang , Gangshan Wu

We study the problem of covering a given set of $n$ points in a high, $d$-dimensional space by the minimum enclosing polytope of a given arbitrary shape. We present algorithms that work for a large family of shapes, provided either only…

Computational Geometry · Computer Science 2007-05-23 Rina Panigrahy

Given a source of iid samples of edges of an input graph $G$ with $n$ vertices and $m$ edges, how many samples does one need to compute a constant factor approximation to the maximum matching size in $G$? Moreover, is it possible to obtain…

Data Structures and Algorithms · Computer Science 2019-07-15 Michael Kapralov , Slobodan Mitrović , Ashkan Norouzi-Fard , Jakab Tardos

According to a result of Arkin~\etal~(2016), given $n$ point pairs in the plane, there exists a simple polygonal cycle that separates the two points in each pair to different sides; moreover, a $O(\sqrt{n})$-factor approximation with…

Computational Geometry · Computer Science 2019-12-04 Adrian Dumitrescu

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

Given an $n$-vertex $m$-edge digraph $G = (V,E)$ and a subset $S \subseteq V$ of $|S| = n^{\sigma}$ (for some $0 \le \sigma \le 1$) designated sources, the $S \times V$ reachability problem is to compute the sets $\mathcal V_s$ of vertices…

Data Structures and Algorithms · Computer Science 2026-05-12 Michael Elkin , Chhaya Trehan

We present a new and surprisingly simple analysis of random-shift decompositions -- originally proposed by Miller, Peng, and Xu [SPAA'13]: We show that decompositions for exponentially growing scales $D = 2^0, 2^1, \ldots,…

Data Structures and Algorithms · Computer Science 2025-10-13 Rasmus Kyng , Maximilian Probst Gutenberg , Tim Rieder

The Word Mover's Distance (WMD) is a metric that measures the semantic dissimilarity between two text documents by computing the cost of moving all words of a source/query document to the most similar words of a target document optimally.…

Machine Learning · Computer Science 2021-03-24 Jesmin Jahan Tithi , Fabrizio Petrini

We present a new $4$-approximation algorithm for the Combinatorial Motion Planning problem which runs in $\mathcal{O}(n^2\alpha(n^2,n))$ time, where $\alpha$ is the functional inverse of the Ackermann function, and a fully distributed…

Discrete Mathematics · Computer Science 2018-05-24 Simran Dokania , Aditya Paliwal , Shrisha Rao
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