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This work addresses the problem of simulating Gaussian random fields that are continuously indexed over a class of metric graphs, termed graphs with Euclidean edges, being more general and flexible than linear networks. We introduce three…

Statistics Theory · Mathematics 2024-04-29 Alfredo Alegría , Xavier Emery , Tobia Filosi , Emilio Porcu

In this paper, we propose to study a new geometric optimization problem called "geometric prototype" in Euclidean space. Given a set of patterns, where each pattern is represented by a (weighted or unweighted) point set, the geometric…

Computational Geometry · Computer Science 2018-04-26 Hu Ding , Manni Liu

Projective geometry provides the preferred framework for most implementations of Euclidean space in graphics applications. Translations and rotations are both linear transformations in projective geometry, which helps when it comes to…

Computational Geometry · Computer Science 2007-05-23 Chris Doran , Anthony Lasenby , Joan Lasenby

Euclidean geometry is among the earliest forms of mathematical thinking. While the geometric primitives underlying its constructions, such as perfect lines and circles, do not often occur in the natural world, humans rarely struggle to…

Computer Vision and Pattern Recognition · Computer Science 2022-12-01 Joy Hsu , Jiajun Wu , Noah D. Goodman

We study surfaces with a constant ratio of principal curvatures in Euclidean and simply isotropic geometries and characterize rotational, channel, ruled, helical, and translational surfaces of this kind under some technical restrictions…

Differential Geometry · Mathematics 2025-10-17 Khusrav Yorov , Mikhail Skopenkov , Helmut Pottmann

We revisit the task of learning a Euclidean metric from data. We approach this problem from first principles and formulate it as a surprisingly simple optimization problem. Indeed, our formulation even admits a closed form solution. This…

Machine Learning · Statistics 2016-07-19 Pourya Habib Zadeh , Reshad Hosseini , Suvrit Sra

This paper examines a variety of classical optimization problems, including well-known minimization tasks and more general variational inequalities. We consider a stochastic formulation of these problems, and unlike most previous work, we…

Optimization and Control · Mathematics 2025-11-11 Vladimir Solodkin , Andrew Veprikov , Aleksandr Beznosikov

In this paper we consider the isoptic curves on the 2-dimensional geometries of constant curvature $\bE^2,~\bH^2,~\cE^2$. The topic is widely investigated in the Euclidean plane $\bE^2$ see for example \cite{CMM91} and \cite{Wi} and the…

Geometric Topology · Mathematics 2013-01-31 Géza Csima , Jenő Szirmai

We present a new numerical method for the isometric embedding of 2-geometries specified by their 2-metrics in three dimensional Euclidean space. Our approach is to directly solve the fundamental embedding equation supplemented by six…

General Relativity and Quantum Cosmology · Physics 2015-06-23 Wolfgang Tichy , Jonathan R. McDonald , Warner A. Miller

We study flexible polyhedral nets in isotropic geometry. This geometry has a degenerate metric, but there is a natural notion of flexibility. We study infinitesimal and finite flexibility, and classify all finitely flexible polyhedral nets…

Metric Geometry · Mathematics 2025-04-22 O. Pirahmad , H. Pottmann , M. Skopenkov

We consider the problem of embedding the nodes of a hypergraph into Euclidean space under the assumption that the interactions arose through closeness to unknown hyperedge centres. In this way, we tackle the inverse problem associated with…

Social and Information Networks · Computer Science 2025-09-11 Francesco Zigliotto , Desmond J. Higham

In this paper we consider the problem of approximating Euclidean distances by the infinite integer grid graph. Although the topology of the graph is fixed, we have control over the edge-weight assignment $w:E\to \mathbb{R}_{\ge 0}$, and…

Computational Geometry · Computer Science 2025-11-25 Zixi Cai , Kuowen Chen , Shengquan Du , Arnold Filtser , Seth Pettie , Daniel Skora

We develop an inversive geometry for anisotropic quadradic spaces, in analogy with the classical inversive geometry of a Euclidean plane.

Commutative Algebra · Mathematics 2022-10-12 Nicholas Phat Nguyen

Many scientific fields study data with an underlying structure that is a non-Euclidean space. Some examples include social networks in computational social sciences, sensor networks in communications, functional networks in brain imaging,…

Computer Vision and Pattern Recognition · Computer Science 2017-08-02 Michael M. Bronstein , Joan Bruna , Yann LeCun , Arthur Szlam , Pierre Vandergheynst

The techniques and analysis presented in this thesis provide new methods to solve optimization problems posed on Riemannian manifolds. These methods are applied to the subspace tracking problem found in adaptive signal processing and…

Optimization and Control · Mathematics 2013-05-09 Steven Thomas Smith

This paper concerns models and convergence principles for dealing with stochasticity in a wide range of algorithms arising in nonlinear analysis and optimization in Hilbert spaces. It proposes a flexible geometric framework within which…

Optimization and Control · Mathematics 2026-02-17 Patrick L. Combettes , Javier I. Madariaga

Isogenies, the mappings of elliptic curves, have become a useful tool in cryptology. These mathematical objects have been proposed for use in computing pairings, constructing hash functions and random number generators, and analyzing the…

Cryptography and Security · Computer Science 2009-10-29 Daniel Shumow

The distance geometry problem asks to find a realization of a given simple edge-weighted graph in a Euclidean space of given dimension K, where the edges are realized as straight segments of lengths equal (or as close as possible) to the…

Optimization and Control · Mathematics 2023-07-31 Leo Liberti , Gabriele Iommazzo , Carlile Lavor , Nelson Maculan

This paper presents a geometric approach to the classical isoperimetric problem by analysing the efficiency of regular polygons in enclosing maximum area for a fixed perimeter. Using efficiency metrics, it proves that regular polygons…

General Mathematics · Mathematics 2025-07-22 Lakshya Chaudhary

We consider the fundamental task of optimising a real-valued function defined in a potentially high-dimensional Euclidean space, such as the loss function in many machine-learning tasks or the logarithm of the probability distribution in…

Machine Learning · Statistics 2024-03-20 Marcelo Hartmann , Bernardo Williams , Hanlin Yu , Mark Girolami , Alessandro Barp , Arto Klami
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