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Related papers: Terminal Embeddings

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We consider the vector embedding problem. We are given a finite set of items, with the goal of assigning a representative vector to each one, possibly under some constraints (such as the collection of vectors being standardized, i.e.,…

Machine Learning · Computer Science 2021-08-26 Akshay Agrawal , Alnur Ali , Stephen Boyd

We study generalizations of classical metric embedding results to the case of quasimetric spaces; that is, spaces that do not necessarily satisfy symmetry. Quasimetric spaces arise naturally from the shortest-path distances on directed…

Data Structures and Algorithms · Computer Science 2016-08-05 Facundo Mémoli , Anastasios Sidiropoulos , Vijay Sridhar

We study the problem of supervised learning a metric space under discriminative constraints. Given a universe $X$ and sets ${\cal S}, {\cal D}\subset {X \choose 2}$ of similar and dissimilar pairs, we seek to find a mapping $f:X\to Y$, into…

Computational Geometry · Computer Science 2019-03-20 Diego Ihara Centurion , Neshat Mohammadi , Anastasios Sidiropoulos

Edit distance is a fundamental measure of distance between strings and has been widely studied in computer science. While the problem of estimating edit distance has been studied extensively, the equally important question of actually…

Data Structures and Algorithms · Computer Science 2018-05-08 Moses Charikar , Ofir Geri , Michael P. Kim , William Kuszmaul

Given an edge-weighted graph $G$ and a subset of vertices $T$ called terminals, an $\alpha$-distance-approximating minor ($\alpha$-DAM) of $G$ is a graph minor $H$ of $G$ that contains all terminals, such that the distance between every…

Data Structures and Algorithms · Computer Science 2025-09-23 Hsien-Chih Chang , Jonathan Conroy

We revisit the issue of low-distortion embedding of metric spaces into the line, and more generally, into the shortest path metric of trees, from the parameterized complexity perspective.Let $M=M(G)$ be the shortest path metric of an edge…

Data Structures and Algorithms · Computer Science 2008-04-21 Michael Fellows , Fedor Fomin , Daniel Lokshtanov , Elena Losievskaja , Frances A. Rosamond , Saket Saurabh

Theoretical results from discrete geometry suggest that normed spaces can abstractly embed finite metric spaces with surprisingly low theoretical bounds on distortion in low dimensions. In this paper, inspired by this theoretical insight,…

Machine Learning · Computer Science 2023-12-05 Diaaeldin Taha , Wei Zhao , J. Maxwell Riestenberg , Michael Strube

The notion of vertex sparsification is introduced in \cite{M}, where it was shown that for any graph $G = (V, E)$ and a subset of $k$ terminals $K \subset V$, there is a polynomial time algorithm to construct a graph $H = (K, E_H)$ on just…

Data Structures and Algorithms · Computer Science 2010-06-24 Moses Charikar , Tom Leighton , Shi Li , Ankur Moitra

We examine the possibility of approximating Maximum Vertex-Disjoint Shortest Paths. In this problem, the input is an edge-weighted (directed or undirected) $n$-vertex graph $G$ along with $k$ terminal pairs…

Data Structures and Algorithms · Computer Science 2025-04-23 Matthias Bentert , Fedor V. Fomin , Petr A. Golovach

We initiate the study of sparse recovery problems under the Earth-Mover Distance (EMD). Specifically, we design a distribution over m x n matrices A such that for any x, given Ax, we can recover a k-sparse approximation to x under the EMD…

Data Structures and Algorithms · Computer Science 2012-10-12 Piotr Indyk , Eric Price

Most of the literature on spanners focuses on building the graph from scratch. This paper instead focuses on adding edges to improve an existing graph. A major open problem in this field is: given a graph embedded in a metric space, and a…

Computational Geometry · Computer Science 2022-12-20 Joachim Gudmundsson , Sampson Wong

For any finite point set in $D$-dimensional space equipped with the 1-norm, we present random linear embeddings to $k$-dimensional space, with a new metric, having the following properties. For any pair of points from the point set that are…

Probability · Mathematics 2020-11-09 Michael P. Casey

We consider the problem of computing the smallest possible distortion for embedding of a given n-point metric space into R^d, where d is fixed (and small). For d=1, it was known that approximating the minimum distortion with a factor better…

Computational Geometry · Computer Science 2009-09-29 Jiri Matousek , Anastasios Sidiropoulos

We give the first non-trivial decremental dynamic embedding of a weighted, undirected graph $G$ into $\ell_p$ space. Given a weighted graph $G$ undergoing a sequence of edge weight increases, the goal of this problem is to maintain a…

Data Structures and Algorithms · Computer Science 2024-08-15 Kiarash Banihashem , MohammadTaghi Hajiaghayi , Dariusz R. Kowalski , Jan Olkowski , Max Springer

Given a finite metric space $(X\cup Y, \mathbf{d})$ the $k$-median problem is to find a set of $k$ centers $C\subseteq Y$ that minimizes $\sum_{p\in X} \min_{c\in C} \mathbf{d}(p,c)$. In general metrics, the best polynomial time algorithm…

Data Structures and Algorithms · Computer Science 2026-03-26 Anne Driemel , Jan Höckendorff , Ioannis Psarros , Christian Sohler , Di Yue

Distance geometry explores the properties of distance spaces that can be exactly represented as the pairwise Euclidean distances between points in $\mathbb{R}^d$ ($d \geq 1$), or equivalently, distance spaces that can be isometrically…

Computational Geometry · Computer Science 2025-03-26 Matthias Bentert , Fedor V. Fomin , Petr A. Golovach , M. S. Ramanujan , Saket Saurabh

This paper studies the minimal dimension required to embed subset memberships ($m$ elements and ${m\choose k}$ subsets of at most $k$ elements) into vector spaces, denoted as Minimal Embeddable Dimension (MED). The tight bounds of MED are…

Machine Learning · Computer Science 2026-01-30 Zihao Wang , Hang Yin , Lihui Liu , Hanghang Tong , Yangqiu Song , Ginny Wong , Simon See

We consider the problem of embedding a finite set of points $\{x_1, \ldots, x_n\} \in \mathbb{R}^d$ that satisfy $\ell_2^2$ triangle inequalities into $\ell_1$, when the points are approximately low-dimensional. Goemans (unpublished,…

Data Structures and Algorithms · Computer Science 2017-06-22 Yuval Rabani , Rakesh Venkat

Graph Sparsification aims at compressing large graphs into smaller ones while preserving important characteristics of the input graph. In this work we study Vertex Sparsifiers, i.e., sparsifiers whose goal is to reduce the number of…

Data Structures and Algorithms · Computer Science 2017-12-29 Gramoz Goranci , Monika Henzinger , Pan Peng

In this paper we study the Steiner tree problem over a dynamic set of terminals. We consider the model where we are given an $n$-vertex graph $G=(V,E,w)$ with positive real edge weights, and our goal is to maintain a tree which is a good…

Data Structures and Algorithms · Computer Science 2016-06-27 Jakub Łącki , Jakub Oćwieja , Marcin Pilipczuk , Piotr Sankowski , Anna Zych