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We characterize uniformly perfect, complete, doubling metric spaces which embed bi- Lipschitzly into Euclidean space. Our result applies in particular to spaces of Grushin type equipped with Carnot-Carath\'eodory distance. Hence we obtain…

Metric Geometry · Mathematics 2011-05-13 Jeehyeon Seo

This short note investigates the compact embedding of degenerate matrix weighted Sobolev spaces into weighted Lebesgue spaces. The Sobolev spaces explored are defined as the abstract completion of Lipschitz functions in a bounded domain…

Analysis of PDEs · Mathematics 2019-08-16 Dario D. Monticelli , Scott Rodney

We establish embeddings on a class of Sobolev spaces with potential weights on unbounded domains. Our results provide embeddings into weighted Lebesgue spaces $L^q_\theta$ with radial power weights and establish the existence and…

Analysis of PDEs · Mathematics 2023-06-02 Joao Marcos do O , Guozhen Lu , Raoni Ponciano

In this paper, we characterize the boundedness and the compactness of weighted composition operators acting on a de Branges-Rovnyak space $\mathcal H(b)$, where the symbol $b$ is a rational function in the unit ball of $H^\infty$ that is…

Complex Variables · Mathematics 2025-12-18 Emmanuel Fricain , Muath Karaki , Javad Mashreghi , Maëva Ostermann

Given a metric space (X, d), we continue our study of the distance function x\mapsto d(x,-) and its relation to bi-Lipschitz embeddings of (X, d) into R^N. As application, given a compact metric-measure space (X, d,\mu), we give three…

Metric Geometry · Mathematics 2025-01-15 H. Movahedi-Lankarani , R. Wells

Learning faithful graph representations as sets of vertex embeddings has become a fundamental intermediary step in a wide range of machine learning applications. We propose the systematic use of symmetric spaces in representation learning,…

Machine Learning · Computer Science 2021-06-10 Federico López , Beatrice Pozzetti , Steve Trettel , Michael Strube , Anna Wienhard

We study equivariant embeddings with small boundary of a given homogeneous space $G/H$, where $G$ is a connected, linear algebraic group with trivial Picard group and only trivial characters, and $H \subset G$ is an extension of a connected…

Algebraic Geometry · Mathematics 2007-05-23 Ivan V. Arzhantsev , Juergen Hausen

We address various topologies (de Bruijn, chordal ring, generalized Petersen, meshes) in various ways ( isometric embedding, embedding up to scale, embedding up to a distance) in a hypercube or a half-hypercube. Example of obtained…

Metric Geometry · Mathematics 2016-11-03 Adel Alahmadi , Husain Alhazmi , Shakir Ali , Michel Deza , Mathieu Dutour Sikirić , Patrick Solé

In this paper, we establish a novel connection between the metric entropy growth and the embeddability of function spaces into reproducing kernel Hilbert/Banach spaces. Metric entropy characterizes the information complexity of function…

Numerical Analysis · Mathematics 2025-08-28 Yiping Lu , Daozhe Lin , Qiang Du

The distance metric plays an important role in nearest neighbor (NN) classification. Usually the Euclidean distance metric is assumed or a Mahalanobis distance metric is optimized to improve the NN performance. In this paper, we study the…

Machine Learning · Statistics 2007-06-26 Bharath K. Sriperumbudur , Gert R. G. Lanckriet

A Hilbert space embedding for probability measures has recently been proposed, wherein any probability measure is represented as a mean element in a reproducing kernel Hilbert space (RKHS). Such an embedding has found applications in…

Machine Learning · Statistics 2010-03-04 Bharath K. Sriperumbudur , Kenji Fukumizu , Gert R. G. Lanckriet

Classical convergence analysis for kernel interpolation typically assumes that the target function $f$ lies in the reproducing kernel Hilbert space $\mathcal{H}_k\!\left(\Omega\right)$ induced by a kernel on a domain…

Numerical Analysis · Mathematics 2025-12-09 Tobias Ehring , Max-Paul Vogel , Bernard Haasdonk

We define distribution spaces of a sequence of convolutions of a set of distributions with smooth functions, the shearlet system. Then, we define associated sequence spaces and prove characterizations. We also show a reproducing identity in…

Functional Analysis · Mathematics 2012-11-06 Daniel Vera

Learning embedding functions, which map semantically related inputs to nearby locations in a feature space supports a variety of classification and information retrieval tasks. In this work, we propose a novel, generalizable and fast method…

Computer Vision and Pattern Recognition · Computer Science 2018-09-05 Hong Xuan , Richard Souvenir , Robert Pless

Instance embeddings are an efficient and versatile image representation that facilitates applications like recognition, verification, retrieval, and clustering. Many metric learning methods represent the input as a single point in the…

Machine Learning · Computer Science 2019-08-28 Seong Joon Oh , Kevin Murphy , Jiyan Pan , Joseph Roth , Florian Schroff , Andrew Gallagher

In this paper we establish inhomogeneous coorbit spaces related to the continuous shearlet transform and the weighted Lebesgue spaces $L_{p,v}, p\geq 1,$ for certain weights $v$. We present an inhomogeneous shearlet frame for…

Numerical Analysis · Mathematics 2017-09-07 Fabian Feise , Lukas Sawatzki

We study the embeddings of (homogeneous and inhomogeneous) anisotropic Besov spaces associated to an expansive matrix $A$ into Sobolev spaces, with focus on the influence of $A$ on the embedding behaviour. For a large range of parameters,…

Functional Analysis · Mathematics 2021-09-17 David Bartusel , Hartmut Führ

In this series of papers we study subspaces of de Branges spaces of entire functions which are generated by majorization on subsets $D$ of the closed upper half-plane. The present, first, part is addressed to the question which subspaces of…

Complex Variables · Mathematics 2010-05-18 Anton Baranov , Harald Woracek

We consider the problem of isometric embedding of metric spaces to the Banach spaces; and introduce and study the remarkable class of so-called linearly rigid metric spaces: these are the spaces that admit a unique, up to isometry, linearly…

Functional Analysis · Mathematics 2008-04-12 J. Melleray , F. V. Petrov , A. M. Vershik

We construct an isometric embedding of a bounded set in a Euclidean space into the Gromov-Hausdorff space. In particular, we can embed a bounded and connected Riemannian manifold into the Gromov-Hausdorff space by a bilipschitz map.

Metric Geometry · Mathematics 2024-10-25 Takuma Byakuno