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This paper is partly an exposition, and partly an extension of our work [1] to the multiparameter case. We consider certain classes of parametrized dynamically defined measures. These are push-forwards, under the natural projection, of…

Dynamical Systems · Mathematics 2024-05-13 Balázs Bárány , Károly Simon , Boris Solomyak , Adam Śpiewak

Differential geometric approaches to the analysis and processing of data in the form of symmetric positive definite (SPD) matrices have had notable successful applications to numerous fields including computer vision, medical imaging, and…

Differential Geometry · Mathematics 2024-06-10 Cyrus Mostajeran , Nathaël Da Costa , Graham Van Goffrier , Rodolphe Sepulchre

We introduce a flexible, categorical framework for large-scale geometry that clarifies basic behaviour of the metric Rips filtration and streamlines some constructions in geometric group theory. The paper has two main parts. First, we…

Metric Geometry · Mathematics 2025-11-21 Robert Tang

Generalized sampling is a recently developed linear framework for sampling and reconstruction in separable Hilbert spaces. It allows one to recover any element in any finite-dimensional subspace given finitely many of its samples with…

Numerical Analysis · Mathematics 2013-01-15 Ben Adcock , Anders C. Hansen , Clarice Poon

In applications with significant class imbalance or asymmetric costs, metrics such as the $F_\beta$-measure, AM measure, Jaccard similarity coefficient, and weighted accuracy offer more suitable evaluation criteria than standard binary…

Machine Learning · Computer Science 2025-12-30 Anqi Mao , Mehryar Mohri , Yutao Zhong

A Wasserstein spaces is a metric space of sufficiently concentrated probability measures over a general metric space. The main goal of this paper is to estimate the largeness of Wasserstein spaces, in a sense to be precised. In a first…

Metric Geometry · Mathematics 2012-07-17 Benoit Kloeckner

We present a general framework to study uniqueness, stability and reconstruction for infinite-dimensional inverse problems when only a finite-dimensional approximation of the measurements is available. For a large class of inverse problems…

Analysis of PDEs · Mathematics 2021-11-10 Giovanni S. Alberti , Matteo Santacesaria

We consider generalized gravitational entropy in various higher derivative theories of gravity dual to four dimensional CFTs using the recently proposed regularization of squashed cones. We derive the universal terms in the entanglement…

High Energy Physics - Theory · Physics 2015-06-17 Arpan Bhattacharyya , Menika Sharma , Aninda Sinha

Covariance matrices have proven highly effective across many scientific fields. Since these matrices lie within the Symmetric Positive Definite (SPD) manifold - a Riemannian space with intrinsic non-Euclidean geometry, the primary challenge…

Machine Learning · Computer Science 2025-04-02 Rui Wang , Shaocheng Jin , Ziheng Chen , Xiaoqing Luo , Xiao-Jun Wu

We consider a very general dilaton-axion system coupled to Einstein-Hilbert gravity in arbitrary dimension and we carry out holographic renormalization for any dimension up to and including five dimensions. This is achieved by developing a…

High Energy Physics - Theory · Physics 2016-02-12 Ioannis Papadimitriou

This paper introduces a broad class of Mirror Descent (MD) and Generalized Exponentiated Gradient (GEG) algorithms derived from trace-form entropies defined via deformed logarithms. Leveraging these generalized entropies yields MD \& GEG…

Machine Learning · Computer Science 2025-10-29 Andrzej Cichocki , Toshihisa Tanaka , Frank Nielsen , Sergio Cruces

We provide upper bounds of the expected Wasserstein distance between a probability measure and its empirical version, generalizing recent results for finite dimensional Euclidean spaces and bounded functional spaces. Such a generalization…

Statistics Theory · Mathematics 2020-01-29 Jing Lei

By recasting metrical geometry in a purely algebraic setting, both Euclidean and non-Euclidean geometries can be studied over a general field with an arbitrary quadratic form. Both an affine and a projective version of this new theory are…

Metric Geometry · Mathematics 2007-05-23 Norman J. Wildberger

The class of generalized Berwald metrics contains the class of Berwald metrics. In this paper, we characterize two-dimensional generalized Berwald $(\alpha, \beta)$-metrics with vanishing S-curvature. Let $F=\alpha\phi(s)$,…

Differential Geometry · Mathematics 2023-01-04 Akbar Tayebi , Faezeh Eslami

We reconstruct all (2+1)D quantum double models of finite groups from their boundary symmetries through the repeated application of a gauging procedure, extending the existing construction for abelian groups. We employ the recently proposed…

Quantum Physics · Physics 2025-12-10 David Blanik , José Garre-Rubio

The mathematical theory of rigidity of body-bar and body-hinge frameworks provides a useful tool for analyzing the rigidity and flexibility of many articulated structures appearing in engineering, robotics and biochemistry. In this paper we…

Metric Geometry · Mathematics 2014-02-04 Bernd Schulze , Shin-ichi Tanigawa

The aim of this work is to provide a construction of generalized local symbols on algebraic curves as morphisms of group schemes. From a closed point of a complete, irreducible and non-singular curve $C$ over a perfect field $k$ as the only…

Algebraic Geometry · Mathematics 2020-07-07 Fernando Pablos Romo

Mutually Unbiased Bases (MUBs) constitute a fundamental geometric structure in quantum theory, known for providing an optimal measurement scheme for quantum state tomography. In prime and prime-power dimensions, analytical constructions of…

Quantum Physics · Physics 2026-04-07 Buğra Gültekin , Solomon B. Samuel , Zafer Gedik

For a given metric measure space $(X,d,\mu)$ we consider finite samples of points, calculate the matrix of distances between them and then reconstruct the points in some finite-dimensional space using the multidimensional scaling (MDS)…

Metric Geometry · Mathematics 2022-08-02 Alexey Kroshnin , Eugene Stepanov , Dario Trevisan

Given a convex and differentiable objective $Q(\M)$ for a real symmetric matrix $\M$ in the positive definite (PD) cone -- used to compute Mahalanobis distances -- we propose a fast general metric learning framework that is entirely…

Machine Learning · Computer Science 2021-06-14 Cheng Yang , Gene Cheung , Wei Hu