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The space of Gaussian measures on a Euclidean space is geodesically convex in the $L^2$-Wasserstein space. This space is a finite dimensional manifold since Gaussian measures are parameterized by means and covariance matrices. By…

Differential Geometry · Mathematics 2009-02-11 Asuka Takatsu

We propose an approach for capturing the signal variability in hyperspectral imagery using the framework of the Grassmann manifold. Labeled points from each class are sampled and used to form abstract points on the Grassmannian. The…

Computer Vision and Pattern Recognition · Computer Science 2015-02-04 Sofya Chepushtanova , Michael Kirby

Euclidean distance geometry is the study of Euclidean geometry based on the concept of distance. This is useful in several applications where the input data consists of an incomplete set of distances, and the output is a set of points in…

Quantitative Methods · Quantitative Biology 2012-05-03 Leo Liberti , Carlile Lavor , Nelson Maculan , Antonio Mucherino

There are two definitions of the measurable functional on the topological vector space: as a linear and measurable real-valued function and as a pointwise limit of the sequence of the continious linear functionals. In general case they are…

Functional Analysis · Mathematics 2016-02-23 Denis Fufaev

We develop parametric classes of covariance functions on linear networks and their extension to graphs with Euclidean edges, i.e., graphs with edges viewed as line segments or more general sets with a coordinate system allowing us to…

Statistics Theory · Mathematics 2019-05-03 Ethan Anderes , Jesper Møller , Jakob G. Rasmussen

This paper develops a new integrated ball (pseudo)metric which provides an intermediary between a chosen starting (pseudo)metric d and the L_p distance in general function spaces. Selecting d as the Hausdorff or Fr\'echet distances, we…

Metric Geometry · Mathematics 2022-09-26 Sami Helander , Petra Laketa , Pauliina Ilmonen , Stanislav Nagy , Germain Van Bever , Lauri Viitasaari

Conformally compact asymptotically hyperbolic metrics have been intensively studied. The goal of this note is to understand what intrinsic conditions on a complete Riemannian manifold (M,g) will ensure that g is asymptotically hyperbolic in…

Differential Geometry · Mathematics 2008-07-11 Eric Bahuaud

We investigate the SL(2,R) invariant geodesic curves with the as- sociated invariant distance function in parabolic geometry. Parabolic geom- etry naturally occurs in the study of SL(2,R) and is placed in between the elliptic and the…

Metric Geometry · Mathematics 2013-02-19 Anastasia V. Kisil

In this paper we develop a rigorous foundation for the study of integration and measures on the space $\mathscr{G}(V)$ of all graphs defined on a countable labelled vertex set $V$. We first study several interrelated $\sigma$-algebras and a…

Classical Analysis and ODEs · Mathematics 2015-06-05 Apoorva Khare , Bala Rajaratnam

For a group hyperbolic relative to virtually nilpotent subgroups, on a cusped graph associated to the group, we construct a random walk whose Martin boundary is the Bowditch boundary of the group. Moreover, the harmonic measure is a…

Group Theory · Mathematics 2022-03-15 Debanjan Nandi

Let $(X, \mathscr{L}, \lambda)$ and $(Y, \mathscr{M}, \mu)$ be finite measure spaces for which there exist $A \in \mathscr{L}$ and $B \in \mathscr{M}$ with either $0 < \lambda(A) < 1 < \lambda(X)$ and $0 < \mu(B) < \mu(Y)$, or the other way…

Functional Analysis · Mathematics 2023-05-08 Dorota Glazowska , Paolo Leonetti , Janusz Matkowski , Salvatore Tringali

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

In this note we present a refinement of the AM-GM inequality, and then we estimate in a special case the typical size of the improvement.

Classical Analysis and ODEs · Mathematics 2009-10-30 J. M. Aldaz

Given a measured lamination on a finite area hyperbolic surface we consider a natural measure Mon the real line obtained by taking the push-forward of the volume measure of the unit tangent bundle of the surface under an intersection…

Geometric Topology · Mathematics 2014-11-11 Martin J. Bridgeman

Objective functions that optimize deep neural networks play a vital role in creating an enhanced feature representation of the input data. Although cross-entropy-based loss formulations have been extensively used in a variety of supervised…

Computer Vision and Pattern Recognition · Computer Science 2023-12-19 Deen Dayal Mohan , Bhavin Jawade , Srirangaraj Setlur , Venu Govindaraj

The geodesic approximation is a powerful method for studying the dynamics of BPS solitons. However, there are systems, such as BPS monopoles in three-dimensional hyperbolic space, where this approach is not applicable because the moduli…

High Energy Physics - Theory · Physics 2022-01-28 Paul Sutcliffe

It is known that PQ-symmetric maps on the boundary characterize the quasi-isometry type of visual hyperbolic spaces, in particular, of geodesically complete \br-trees. We define a map on pairs of PQ-symmetric ultrametric spaces which…

Geometric Topology · Mathematics 2010-02-08 Álvaro Martínez-Pérez

We provide examples of transitive partially hyperbolic dynamics (specific but paradigmatic examples of homoclinic classes) which blend different types of hyperbolicity in the one-dimensional center direction. These homoclinic classes have…

Dynamical Systems · Mathematics 2018-05-21 Lorenzo J. Díaz , Katrin Gelfert , Tiane Marcarini , Michał Rams

In a recent paper A. Cianchi, N. Fusco, F. Maggi, and A. Pratelli have shown that, in the Gauss space, a set of given measure and almost minimal Gauss boundary measure is necessarily close to be a half-space. Using only geometric tools, we…

Probability · Mathematics 2011-03-24 Yohann de Castro

The cognitive framework of conceptual spaces [3] provides geometric means for representing knowledge. A conceptual space is a high-dimensional space whose dimensions are partitioned into so-called domains. Within each domain, the Euclidean…

Artificial Intelligence · Computer Science 2017-09-25 Lucas Bechberger
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