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In this paper we study the Spanning Tree Congestion problem, where we are given a graph $G=(V,E)$ and are asked to find a spanning tree $T$ of minimum maximum congestion. Here, the congestion of an edge $e\in T$ is the number of edges…

Data Structures and Algorithms · Computer Science 2026-05-28 Michael Lampis , Valia Mitsou , Edouard Nemery , Yota Otachi , Manolis Vasilakis , Daniel Vaz

Let $P$ be a set of $n$ points in $\mathbb{R}^3$ in general position, and let $RCH(P)$ be the rectilinear convex hull of $P$. In this paper we obtain an optimal $O(n\log n)$-time and $O(n)$-space algorithm to compute $RCH(P)$. We also…

Computational Geometry · Computer Science 2022-09-14 Pablo Pérez-Lantero , Carlos Seara , Jorge Urrutia

A convex geometric graph is a graph whose vertices are the corners of a convex polygon P in the plane and whose edges are boundary edges and diagonals of the polygon. It is called triangulation-free if its non-boundary edges do not contain…

Combinatorics · Mathematics 2025-08-19 David Garber , Chaya Keller , Olga Nissenbaum , Shimon Aviram

Embedding the vertices of arbitrary graphs into trees while minimizing some measure of overlap is an important problem with applications in computer science and physics. In this work, we consider the problem of bijectively embedding the…

Data Structures and Algorithms · Computer Science 2026-05-13 Sayan Mukherjee , Shinichiro Akiyama

Given a convex polyhedral surface P, we define a tailoring as excising from P a simple polygonal domain that contains one vertex v, and whose boundary can be sutured closed to a new convex polyhedron via Alexandrov's Gluing Theorem. In…

Metric Geometry · Mathematics 2022-05-24 Joseph O'Rourke , Costin Vilcu

Many years ago John Tyrell a lecturer at King's college London challenged his Ph.D. students with the following puzzle: show that there is a unique triangle of minimal perimeter with exactly one vertex to lie on one of three given lines,…

Optimization and Control · Mathematics 2026-01-21 Triloki Nath , Manohar Choudhary , Ram K. Pandey

We study the problem of $2$-dimensional orthogonal range counting with additive error. Given a set $P$ of $n$ points drawn from an $n\times n$ grid and an error parameter $\eps$, the goal is to build a data structure, such that for any…

Data Structures and Algorithms · Computer Science 2016-05-24 Zhewei Wei , Ke Yi

The problem of finding suitable point embedding or geometric configurations given only Euclidean distance information of point pairs arises both as a core task and as a sub-problem in a variety of machine learning applications. In this…

Machine Learning · Computer Science 2024-10-23 Ipsita Ghosh , Abiy Tasissa , Christian Kümmerle

We present a new approach to learning the structure and parameters of a Bayesian network based on regularized estimation in an exponential family representation. Here we show that, given a fixed variable order, the optimal structure and…

Machine Learning · Computer Science 2012-07-02 Yuhong Guo , Dale Schuurmans

A common representation of a three dimensional object in computer applications, such as graphics and design, is in the form of a triangular mesh. In many instances, individual or groups of triangles in such representation need to satisfy…

Optimization and Control · Mathematics 2019-04-08 Valentin R. Koch , Hung M. Phan

Geometric data structures have been extensively studied in the regime where the dimension is much smaller than the number of input points. But in many scenarios in Machine Learning, the dimension can be much higher than the number of points…

Data Structures and Algorithms · Computer Science 2025-04-07 Martin G. Herold , Danupon Nanongkai , Joachim Spoerhase , Nithin Varma , Zihang Wu

Contact graphs of isothetic rectangles unify many concepts from applications including VLSI and architectural design, computational geometry, and GIS. Minimizing the area of their corresponding {\em rectangular layouts} is a key problem. We…

Data Structures and Algorithms · Computer Science 2007-05-23 Adam L. Buchsbaum , Emden R. Gansner , Cecilia M. Procopiuc , Suresh Venkatasubramanian

We present two parallel optimization algorithms for a convex function $f$. The first algorithm optimizes over linear inequality constraints in a Hilbert space, $\mathbb H$, and the second over a non convex polyhedron in $\mathbb R^n$. The…

Optimization and Control · Mathematics 2025-10-22 E. Dov Neimand , Serban Sabau

Let $P$ be a set of $n$ points in general position on the plane. A set of closed convex polygons with vertices in $P$, and with pairwise disjoint interiors is called a convex decomposition of $P$ if their union is the convex hull of $P$,…

Combinatorics · Mathematics 2019-09-16 Toshinori Sakai , Jorge Urrutia

A frame is a generalization of a basis of a vector space to a redundant overspanning set whose vectors are linearly dependent. Frames find applications in signal processing and quantum information theory. We present a genetic algorithm that…

Computational Physics · Physics 2025-08-13 Sebastián Roca-Jerat , Juan Román-Roche

We present a mathematical and algorithmic scheme for learning the principal geometric elements in an image or 3D object. We build on recent work that convexifies the basic problem of finding a combination of a small number shapes that…

Computer Vision and Pattern Recognition · Computer Science 2016-07-05 Alireza Aghasi , Justin Romberg

We present efficient data structures for approximate nearest neighbor searching and approximate 2-point shortest path queries in a two-dimensional polygonal domain $P$ with $n$ vertices. Our goal is to store a dynamic set of $m$ point sites…

Computational Geometry · Computer Science 2026-03-13 Joost van der Laan , Frank Staals , Lorenzo Theunissen

Let $k \geq 2$ be a constant. Given any $k$ convex polygons in the plane with a total of $n$ vertices, we present an $O(n\log^{2k-3}n)$ time algorithm that finds a translation of each of the polygons such that the area of intersection of…

Computational Geometry · Computer Science 2023-07-04 Hyuk Jun Kweon , Honglin Zhu

Neural models learn representations of high-dimensional data on low-dimensional manifolds. Multiple factors, including stochasticities in the training process, model architectures, and additional inductive biases, may induce different…

Machine Learning · Computer Science 2025-12-02 Hanlin Yu , Berfin Inal , Georgios Arvanitidis , Soren Hauberg , Francesco Locatello , Marco Fumero

Geometric embedding of graphs in a point set in the plane is a well known problem. In this paper, the complexity of a variant of this problem, where the point set is bounded by a simple polygon, is considered. Given a point set in the plane…

Computational Geometry · Computer Science 2009-08-28 Alireza Bagheri , Mohammadreza Razzazi
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