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Transfer learning for feature extraction can be used to exploit deep representations in contexts where there is very few training data, where there are limited computational resources, or when tuning the hyper-parameters needed for training…

In this paper we derive necessary and sufficient conditions for a smooth surface in Rn+1 to admit a local 1-quasiconformal parameterization by a domain in Rn (n >= 3). We then apply these conditions to specific hypersurfaces such as…

Classical Analysis and ODEs · Mathematics 2018-01-03 Tao Cheng , Huanhuan Yang , Shanshuang Yang

This study focuses on Concave mappings, a class of univalent functions that exhibit a unique property: they map the unit disk onto a domain whose complement is convex. The main objective of this work is to characterize these mappings in…

Complex Variables · Mathematics 2023-08-17 V. Bravo , R. Hernández , O. Venegas

We prove bounds for the covering numbers of classes of convex functions and convex sets in Euclidean space. Previous results require the underlying convex functions or sets to be uniformly bounded. We relax this assumption and replace it…

Information Theory · Computer Science 2014-10-24 Adityanand Guntuboyina

A bounded domain $K \subset \mathbb R^n$ is called polynomially integrable if the $(n-1)$-dimensional volume of the intersection $K$ with a hyperplane $\Pi$ polynomially depends on the distance from $\Pi$ to the origin. It was proved in [7]…

Functional Analysis · Mathematics 2022-11-24 Mark Agranovsky , Alexander Koldobsky , Dmitry Ryabogin , Vladyslav Yaskin

Regular variation of a multivariate measure with a Lebesgue density implies the regular variation of its density provided the density satisfies some regularity conditions. Unlike the univariate case, the converse also requires regularity…

Probability · Mathematics 2016-01-12 Tiandong Wang , Sidney I. Resnick

We analyze the embedding dimension of a normal weighted homogeneous surface singularity, and more generally, the Poincar\'e series of the minimal set of generators of the graded algebra of regular functions, provided that the link of the…

Algebraic Geometry · Mathematics 2025-12-16 András Némethi , Tomohiro Okuma

We derive an upper bound on the size of a ball such that the image of the ball under quadratic map is strongly convex and smooth. Our result is the best possible improvement of the analogous result by Polyak in the case of quadratic map. We…

Optimization and Control · Mathematics 2017-10-27 Anatoly Dymarsky

Convolution is an efficient technique to obtain abstract feature representations using hierarchical layers in deep networks. Although performing convolution in Euclidean geometries is fairly straightforward, its extension to other…

Machine Learning · Computer Science 2019-01-04 Sameera Ramasinghe , Salman Khan , Nick Barnes

Principal Component Analysis can be performed over small domains of an embedded Riemannian manifold in order to relate the covariance analysis of the underlying point set with the local extrinsic and intrinsic curvature. We show that the…

Differential Geometry · Mathematics 2018-04-30 Javier Álvarez-Vizoso , Michael Kirby , Chris Peterson

Sobolev embeddings, of arbitrary order, are considered into function spaces on domains of $\mathbb R^n$ endowed with measures whose decay on balls is dominated by a power $d$ of their radius. Norms in arbitrary rearrangement-invariant…

Functional Analysis · Mathematics 2019-12-10 Andrea Cianchi , Luboš Pick , Lenka Slavíková

We prove that any Loewner PDE in a complete hyperbolic starlike domain of $\C^N$ (in particular in bounded convex domains) admits an essentially unique univalent solution with values in $\C^N$.

Complex Variables · Mathematics 2012-07-12 Leandro Arosio , Filippo Bracci , Erlend Fornaess Wold

In this paper we introduce a general version of the notion of Loewner chains which comes from the new and unified treatment, given in [arXiv:0807.1594], of the radial and chordal variant of the Loewner differential equation, which is of…

Complex Variables · Mathematics 2009-02-19 Manuel D. Contreras , Santiago Diaz-Madrigal , Pavel Gumenyuk

In this paper we confirm that several crucial theorems due to Pommerenke and Becker for the theory of Loewner chains work well without normalization on the complex-valued first coefficient. As applications of those considerations, some new…

Complex Variables · Mathematics 2010-10-11 Ikkei Hotta

This paper addresses the task of learning convex regularizers to guide the reconstruction of images from limited data. By imposing that the reconstruction be amplitude-equivariant, we narrow down the class of admissible functionals to those…

Machine Learning · Statistics 2026-01-19 Michael Unser , Stanislas Ducotterd

Convolution is an integral operation that defines how the shape of one function is modified by another function. This powerful concept forms the basis of hierarchical feature learning in deep neural networks. Although performing convolution…

Computer Vision and Pattern Recognition · Computer Science 2019-12-04 Sameera Ramasinghe , Salman Khan , Nick Barnes , Stephen Gould

Given a set $\mathfrak S$ of conformal maps of the unit disk $\mathbb D$ into itself that is closed under composition, we address the question whether $\mathfrak S$ can be represented as the reachable set of a Loewner - Kufarev - type ODE…

Complex Variables · Mathematics 2017-04-05 Pavel Gumenyuk

It is proved that any smooth manifold $\mathcal M$ of dimension $m$ admits a smooth polynomially convex embedding into $\mathbb C^n$ when $n\geq \lfloor 5m/4\rfloor$. Further, such embeddings are dense in the space of smooth maps from…

Complex Variables · Mathematics 2025-04-03 Purvi Gupta , Rasul Shafikov

There exists a proper holomorphic mapping between balls of different dimensions such that it does not extend continuously to the boundary. The aim of this paper is to show the same phenomenon occurs for pseudoconvex domains of different…

Complex Variables · Mathematics 2024-06-07 Atsushi Hayashimoto

We study renormalization of highly dissipative analytic three dimensional H\'enon maps $$ F(x,y,z) = (f(x) - \varepsilon(x,y,z),\ x,\ \delta(x,y,z)) $$ where $ \varepsilon(x,y,z) $ is a sufficiently small perturbation of $…

Dynamical Systems · Mathematics 2014-12-30 Young Woo Nam