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Related papers: Stiefel manifolds and polygons

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We build a new probability measure on closed space and plane polygons. The key construction is a map, given by Knutson and Hausmann using the Hopf map on quaternions, from the complex Stiefel manifold of 2-frames in n-space to the space of…

Differential Geometry · Mathematics 2019-10-23 Jason Cantarella , Tetsuo Deguchi , Clayton Shonkwiler

The field of numerical algebraic geometry consists of algorithms for numerically solving systems of polynomial equations. When the system is exact, such as having rational coefficients, the solution set is well-defined. However, for a…

Numerical Analysis · Mathematics 2024-03-28 Emma R. Cobian , Jonathan D. Hauenstein , Charles W. Wampler

System identification of autoregressive processes on Stiefel and Grassmann manifolds are presented and studied. We define the system parameters as elements in the orthogonal group and we show that the system can be estimated by averaging…

Statistics Theory · Mathematics 2025-11-05 Jordi-Lluís Figueras , Aron Persson

There are (at least) two reasons to study random polytopes. The first is to understand the combinatorics and geometry of random polytopes especially as compared to other classes of polytopes, and the second is to analyze average-case…

Probability · Mathematics 2019-05-02 Andrew Newman

Finite frames can be viewed as mass points distributed in $N$-dimensional Euclidean space. As such they form a subclass of a larger and rich class of probability measures that we call probabilistic frames. We derive the basic properties of…

Probability · Mathematics 2017-09-04 Martin Ehler , Kasso A. Okoudjou

It is argued that spectral features of quantal systems with random interactions can be given a geometric interpretation. This conjecture is investigated in the context of two simple models: a system of randomly interacting d bosons and one…

Nuclear Theory · Physics 2009-11-10 P. Chau Huu-Tai , A. Frank , N. A. Smirnova , P. Van Isacker

We argue for more widespread use of manifold-like polyfolds (M-polyfolds) as differential geometric objects. M-polyfolds possess a distinct advantage over differentiable manifolds, enabling a smooth and local change of dimension. To…

Differential Geometry · Mathematics 2025-03-25 Per Åhag , Rafał Czyż , Håkan Samuelsson Kalm , Aron Persson

In this paper we develop new Newton and conjugate gradient algorithms on the Grassmann and Stiefel manifolds. These manifolds represent the constraints that arise in such areas as the symmetric eigenvalue problem, nonlinear eigenvalue…

Computational Physics · Physics 2009-09-25 Alan Edelman , T. A. Arias , Steven T. Smith

We study the rational approximation properties of special manifolds defined by a set of polynomials with rational coefficients. Mostly we will assume the case of all polynomials to depend on only one variable. In this case the manifold can…

Number Theory · Mathematics 2018-12-31 Johannes Schleischitz

A central issue of the science of complex systems is the quantitative characterization of complexity. In the present work we address this issue by resorting to information geometry. Actually we propose a constructive way to associate to a -…

Mathematical Physics · Physics 2017-12-19 Roberto Franzosi , Domenico Felice , Stefano Mancini , Marco Pettini

This entry contains the core material of my habilitation thesis, soon to be officially submitted. It provides a self-contained presentation of the original results in this thesis, in addition to their detailed proofs. The motivation of…

Statistics Theory · Mathematics 2021-01-27 Salem Said

Many techniques in machine learning attempt explicitly or implicitly to infer a low-dimensional manifold structure of an underlying physical phenomenon from measurements without an explicit model of the phenomenon or the measurement…

Machine Learning · Statistics 2023-07-04 Roy R. Lederman , Bogdan Toader

Contours may be viewed as the 2D outline of the image of an object. This type of data arises in medical imaging as well as in computer vision and can be modeled as data on a manifold and can be studied using statistical shape analysis.…

Applications · Statistics 2017-05-17 Chalani Prematilake , Leif Ellingson

Meta-learning, or "learning to learn," aims to enable models to quickly adapt to new tasks with minimal data. While traditional methods like Model-Agnostic Meta-Learning (MAML) optimize parameters in Euclidean space, they often struggle to…

Machine Learning · Computer Science 2025-03-17 JuneYoung Park , YuMi Lee , Tae-Joon Kim , Jang-Hwan Choi

The interpolation of couples of separable Hilbert spaces with a function parameter is studied. The main properties of the classic interpolation are proved. Some applications to the interpolation of isotropic H\"ormander spaces over a closed…

Analysis of PDEs · Mathematics 2009-03-30 Vladimir A. Mikhailets , Alexandr A. Murach

Given a closed real analytic Riemannian manifold, we construct and study a one parameter family of adapted complex structures on the manifold of its geodesics.

Complex Variables · Mathematics 2014-02-26 László Lempert , Róbert Szőke

Parametrizations of data manifolds in shape spaces can be computed using the rich toolbox of Riemannian geometry. This, however, often comes with high computational costs, which raises the question if one can learn an efficient neural…

Machine Learning · Computer Science 2023-09-04 Josua Sassen , Klaus Hildebrandt , Martin Rumpf , Benedikt Wirth

Hypergraphs are structures that can be decomposed or described; in other words they are recursively countable. Here, we get exact and asymptotic enumeration results on hypergraphs by means of exponential generating functions. The number of…

Discrete Mathematics · Computer Science 2008-06-20 Tsiriniaina Andriamampianina

Random packing of unoriented regular polygons and star polygons on a two-dimensional flat, continuous surface is studied numerically using random sequential adsorption algorithm. Obtained results are analyzed to determine saturated random…

Statistical Mechanics · Physics 2016-03-27 Michał Cieśla , Jakub Barbasz

Polygon spaces have been studied extensively, and yet missing from the literature is a simple property that every polygon has: dimension. This is distinct (possibly) from the dimension of the ambient space in which the polygon lives. A…

General Topology · Mathematics 2020-09-17 Jack Love