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It is shown that a formal mapping between two real-analytic hypersurfaces in complex space is convergent provided that neither hypersurface contains a nontrivial holomorphic variety. For higher codimensional generic submanifolds,…

Complex Variables · Mathematics 2007-05-23 M. S. Baouendi , P. Ebenfelt , L. P. Rothschild

It is well-known that a homomorphism p between topological groups K, G is a covering homomorphism if and only if p is an open epimorphism with discrete kernel. In this paper we generalize this fact, in precisely, we show that for a…

Algebraic Topology · Mathematics 2018-08-28 Hamid Torabi , Mehdi Abdullahi Rashid , Majid Kowkabi

We present a geometric algorithm to compute the geometric kernel of a generic polyhedron. The geometric kernel (or simply kernel) is definedas the set of points from which the whole polyhedron is visible. Whilst the computation of the…

Computational Geometry · Computer Science 2021-10-28 Tommaso Sorgente , Silvia Biasotti , Michela Spagnuolo

In this paper we study the set of projective maps between compact proper convex real projective manifolds. We show that this set contains only finitely many distinct homotopy classes and each homotopy class has the structure of a real…

Differential Geometry · Mathematics 2015-07-01 Andrew Zimmer

We prove that many normal subgroups of the extended mapping class group of a surface with punctures are geometric, that is, that their automorphism groups and abstract commensurator groups are isomorphic to the extended mapping class group.…

Geometric Topology · Mathematics 2018-10-02 Alan McLeay

We show that a closed orientable 3--dimensional manifold admits a round fold map into the plane, i.e. a fold map whose critical value set consists of disjoint simple closed curves isotopic to concentric circles, if and only if it is a graph…

Geometric Topology · Mathematics 2023-11-15 Naoki Kitazawa , Osamu Saeki

Recent work has identified non-compact symmetric spaces U/H as a promising class of homogeneous manifolds to develop a geometrically consistent theory of neural networks. An initial implementation of these concepts has been presented in a…

Machine Learning · Computer Science 2025-07-24 Pietro Giuseppe Fré , Federico Milanesio , Guido Sanguinetti , Matteo Santoro

Given a connected, compact, totally geodesic submanifold Y^m of noncompact type inside a compact locally symmetric space of noncompact type X^n, we provide a sufficient condition that ensures that [Y^m] is nonzero in H_m(X^n; R); in low…

Geometric Topology · Mathematics 2009-07-29 Jean-Francois Lafont , Benjamin Schmidt

Let $S$ be a hyperbolic oriented Riemann surface of finite type. The main purpose of this paper is to show that non-trivial geometric intersection between closed curves on $S$ is detected by some symplectic submodules they naturally…

Algebraic Topology · Mathematics 2024-06-14 Marco Boggi , Pavel Zalesskii

A simple surface amalgam is the union of a finite collection of surfaces with precisely one boundary component each and which have their boundary curves identified. We prove if two fundamental groups of simple surface amalgams act properly…

Geometric Topology · Mathematics 2018-12-05 Emily Stark , Daniel Woodhouse

Modern machine learning systems are increasingly trained on large amounts of data embedded in high-dimensional spaces. Often this is done without analyzing the structure of the dataset. In this work, we propose a framework to study the…

Machine Learning · Computer Science 2023-04-27 Carlos Hurtado , Sarath Shekkizhar , Javier Ruiz-Hidalgo , Antonio Ortega

Applying kernel methods to matchings is challenging due to their discrete, non-Euclidean nature. In this paper, we develop a principled framework for constructing geometric kernels that respect the natural geometry of the space of…

Machine Learning · Computer Science 2026-04-17 Dmitry Eremeev , Salem Said , Viacheslav Borovitskiy

We present sufficient condition for a family of positive definite kernels on a compact two-point homogeneous space to be strictly positive definite based on their representation as a series of spherical harmonics. The family analyzed is a…

Classical Analysis and ODEs · Mathematics 2022-05-17 Jean Carlo Guella , Janin Jäger

Let $\Gamma_g$ be the fundamental group of a closed connected orientable surface of genus $g\geq2$. We introduce a combinatorial structure of "core surfaces", that represent subgroups of $\Gamma_g$. These structures are (usually)…

Group Theory · Mathematics 2022-06-22 Michael Magee , Doron Puder

A graph is geometric 1-planar if it admits a straight-line drawing where each edge is crossed at most once. We provide the first systematic study of the parameterized complexity of recognizing geometric 1-planar graphs. By substantially…

Computational Complexity · Computer Science 2026-02-11 Alexander Firbas

We give a necessary condition of geometric nature for the existence of the $H$-fractional Brownian field indexed by a Riemannian manifold. In the case of the L\'evy Brownian field ($H=1/2$) indexed by manifolds with minimal closed geodesics…

Probability · Mathematics 2017-06-02 Nil Venet

An independent vertex subset $S$ of the directed graph $G$ is a kernel if the set of out-neighbors of $S$ is $V(G)\setminus S$. An independent vertex subset $Q$ of $G$ is a quasi-kernel if the union of the first and second out-neighbors…

Combinatorics · Mathematics 2024-05-30 Péter L. Erdős , Ervin Győri , Tamás Róbert Mezei , Nika Salia , Mykhaylo Tyomkyn

We prove that there is an algorithm which determines whether or not a given 2-polyhedron can be embedded into some integral homology 3-sphere. This is a corollary of the following main result. Let $M$ be a compact connected orientable…

Geometric Topology · Mathematics 2016-06-03 Dmitry Tonkonog

Herein we prove that if $M$ is a compact oriented Riemann surface of genus $g$, and $M^{[n]}$ is the classifying space of $n$ distinct, unordered points on $M$, then the kernel of the map $\pi_1(M^{[n]})\to H_1(M)$ is generated by…

Group Theory · Mathematics 2007-05-23 D. Jeremy Copeland

Kernel methods are powerful tools in machine learning. Classical kernel methods are based on positive-definite kernels, which map data spaces into reproducing kernel Hilbert spaces (RKHS). For non-Euclidean data spaces, positive-definite…

Machine Learning · Computer Science 2024-07-31 Nathael Da Costa , Cyrus Mostajeran , Juan-Pablo Ortega , Salem Said