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This is the first article in a series of two papers in which we study the Temperleyan dimer model on an arbitrary bounded Riemann surface of finite topolgical type. The end goal of both papers is to prove the convergence of height…

Probability · Mathematics 2024-07-24 Nathanaël Berestycki , Benoit Laslier , Gourab Ray

We present a simple, accurate method for computing singular or nearly singular integrals on a smooth, closed surface, such as layer potentials for harmonic functions evaluated at points on or near the surface. The integral is computed with…

Numerical Analysis · Mathematics 2020-02-10 J. Thomas Beale , Wenjun Ying , Jason R. Wilson

An interesting problem in classical differential geometry is to find methods to prove that two surfaces defined by different charts actually coincide up to position in space. In a previous paper we proposed a method in this direction for…

Differential Geometry · Mathematics 2014-12-18 Ognian Kassabov

Embedded minimal surfaces of finite total curvature in $\mathbb{R}^3$ are reasonably well understood: From far away, they look like intersecting catenoids and planes, suitably desingularized. We consider the larger class of harmonic…

Differential Geometry · Mathematics 2014-07-11 Peter Connor , Kevin Li , Matthias Weber

The Banach-Picard iteration is widely used to find fixed points of locally contractive (LC) maps. This paper extends the Banach-Picard iteration to distributed settings; specifically, we assume the map of which the fixed point is sought to…

Optimization and Control · Mathematics 2021-12-30 Francisco L. Andrade , Mário A. T. Figueiredo , João Xavier

We decrease the $rms$ mean curvature and area of a variable surface with a fixed boundary by iterating a few times through a curvature-based variational algorithm. For a boundary with a known minimal surface, starting with a deliberately…

Differential Geometry · Mathematics 2018-03-28 Daud Ahmad , Bilal Masud

Linear regression in $\ell_p$-norm is a canonical optimization problem that arises in several applications, including sparse recovery, semi-supervised learning, and signal processing. Generic convex optimization algorithms for solving…

Data Structures and Algorithms · Computer Science 2020-01-13 Deeksha Adil , Richard Peng , Sushant Sachdeva

With the recent development of high-end LiDARs, more and more systems are able to continuously map the environment while moving and producing spatially redundant information. However, none of the previous approaches were able to effectively…

Robotics · Computer Science 2017-09-19 Chanoh Park , Soohwan Kim , Peyman Moghadam , Clinton Fookes , Sridha Sridharan

An iterative numerical method to compute the conformal mapping in the context of propagating water waves over uneven topographies is investigated. The map flattens the fluid domain onto a canonical strip in which computations are performed.…

Fluid Dynamics · Physics 2021-03-04 Marcelo V. Flamarion , Roberto Ribeiro-Jr

The central purpose of this article is to establish new inverse and implicit function theorems for differentiable maps with isolated critical points. One of the key ingredients is a discovery of the fact that differentiable maps with…

Classical Analysis and ODEs · Mathematics 2021-04-02 Liangpan Li

Robust subspace estimation is fundamental to many machine learning and data analysis tasks. Iteratively Reweighted Least Squares (IRLS) is an elegant and empirically effective approach to this problem, yet its theoretical properties remain…

Machine Learning · Statistics 2026-03-11 Gilad Lerman , Kang Li , Tyler Maunu , Teng Zhang

We consider the task of drawing a graph on multiple horizontal layers, where each node is assigned a layer, and each edge connects nodes of different layers. Known algorithms determine the orders of nodes on each layer to minimize crossings…

Data Structures and Algorithms · Computer Science 2025-03-03 Alexander Dobler , Jakob Roithinger

In this paper, we propose a federated algorithm for solving large linear systems that is inspired by the classic randomized Kaczmarz algorithm. We provide convergence guarantees of the proposed method, and as a corollary of our analysis, we…

Numerical Analysis · Mathematics 2025-05-15 Halyun Jeong , Deanna Needell , Chi-Hao Wu

The paper investigates two inertial extragradient algorithms for seeking a common solution to a variational inequality problem involving a monotone and Lipschitz continuous mapping and a fixed point problem with a demicontractive mapping in…

Optimization and Control · Mathematics 2023-08-08 Bing Tan , Liya Liu , Xiaolong Qin

This paper develops a theory of Lipschitz comparisons of hyperbolic surfaces analogous to the theory of quasi-conformal comparisons. Extremal Lipschitz maps (minimal stretch maps) and geodesics for the `Lipschitz metric' are constructed.…

Geometric Topology · Mathematics 2007-05-23 William P. Thurston

We introduce a notion of a bounded ideal triangulation of an infinite Riemann surface and parametrize Teichm\"uller spaces of infinite surfaces which allow bounded triangulations. We prove that our parametrization is real-analytic. Riemann…

Geometric Topology · Mathematics 2025-02-11 Casey Whitney , Dragomir Saric

We introduce a function model for the Teichm\"uller space of a closed hyperbolic Riemann surface. Then we introduce a new metric by using the maximum norm on the function space on the Teichm\"uller space. We prove that the identity map from…

Complex Variables · Mathematics 2020-06-02 Yunping Jiang

In this investigation we focus on the problem of mapping the ground reflectivity with multiple laser scanners mounted on mobile robots/vehicles. The problem originates because regions of the ground become populated with a varying number of…

Computer Vision and Pattern Recognition · Computer Science 2017-03-10 Juan Castorena

In this note we aim at putting more emphasis on the fact that trying to solve non-convex optimization problems with coordinate-descent iterative linear matrix inequality algorithms leads to suboptimal solutions, and put forward other…

Optimization and Control · Mathematics 2024-10-30 Emile Simon , Vincent Wertz

We investigate the problem of recovering a partially observed high-rank matrix whose columns obey a nonlinear structure such as a union of subspaces, an algebraic variety or grouped in clusters. The recovery problem is formulated as the…

Machine Learning · Statistics 2022-12-12 Florentin Goyens , Coralia Cartis , Armin Eftekhari
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