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We consider the local analytic behavior for a family of holomorphic differentials on a family of degenerating annuli. Three results and discussion are presented. The first is the normal families Lemma 1. The second is an isomorphism of…

Geometric Topology · Mathematics 2011-11-24 Scott A. Wolpert

Marginalising over families of Gaussian Process kernels produces flexible model classes with well-calibrated uncertainty estimates. Existing approaches require likelihood evaluations of many kernels, rendering them prohibitively expensive…

Machine Learning · Statistics 2023-03-16 Saad Hamid , Sebastian Schulze , Michael A. Osborne , Stephen J. Roberts

The article examines a set of irreducible germs $f_P:U_P\to V_p$ of %finite generic morphisms $f:S\to\mathbb P^2$ to the projective plane whose branch curve germs $B_P\subset V_p$ have singularities equisingular deformation equivalent to…

Algebraic Geometry · Mathematics 2025-03-11 Vik. S. Kulikov

In graph theory, the Szemer\'edi regularity lemma gives a decomposition of the indicator function for any graph $G$ into a structured component, a uniform part, and a small error. This result, in conjunction with a counting lemma that…

Combinatorics · Mathematics 2018-11-22 Sammy Luo

We study the problem of testing, using only a single sample, between mean field distributions (like Curie-Weiss, Erd\H{o}s-R\'enyi) and structured Gibbs distributions (like Ising model on sparse graphs and Exponential Random Graphs). Our…

Statistics Theory · Mathematics 2018-05-24 Guy Bresler , Dheeraj Nagaraj

In the study of equisingularity of families of mappings Gaffney introduced the crucial notion of excellent unfoldings. This definition essentially says that the family can be stratified so that there are no strata of dimension 1 other than…

Algebraic Geometry · Mathematics 2008-07-03 Kevin Houston

We present the discrete version of heat kernel smoothing on graph data structure. The method is used to smooth data in an irregularly shaped domains in 3D images. New statistical properties are derived. As an application, we show how to…

Methodology · Statistics 2017-10-24 Moo K. Chung , Yanli Wang , Gurong Wu

We consider the problem of extending germs of plane holomorphic foliations to foliations of compact surfaces. We show that the germs that become regular after a single blow up and admit meromorphic first integrals can be extended, after…

Complex Variables · Mathematics 2014-07-31 Gabriel Calsamiglia , Paulo Sad

In this paper, we are interested in constructing general graph-based regularizers for multiple kernel learning (MKL) given a structure which is used to describe the way of combining basis kernels. Such structures are represented by…

Machine Learning · Statistics 2014-02-14 Ziming Zhang

In this note we prove that a smooth order satisfying the reverse geometric engineering of singularities conditions in stringtheory (in any compactifying dimension) is Auslander regular. Moreover, we classify the etale local structure of…

Rings and Algebras · Mathematics 2007-05-23 Raf Bocklandt , Lieven Le Bruyn , Stijn Symens

A polar hypersurface P of a complex analytic hypersurface germ, f=0, can be investigated by analyzing the invariance of certain Newton polyhedra associated to the image of P, with respect to suitable coordinates, by certain morphisms…

Algebraic Geometry · Mathematics 2007-05-23 Pedro Daniel Gonzalez Perez , Evelia Garcia Barroso

Consider a singular holomorphic map-germ $f: (X,\underline{0}) \to (\mathbb C,0)$ where $X$ is a singular complex analytic variety in $\mathbb C^N$, and another holomorphic map-germ $g: (X,\underline{0}) \to (\mathbb C,0)$ which is…

Algebraic Geometry · Mathematics 2025-10-20 Lê Dũng Tráng , Juan J. Nuño-Ballesteros , José Seade

We introduce an intrinsic notion of Hoelder-Zygmund regularity for Colombeau generalized functions. In case of embedded distributions belonging to some Zygmund-Hoelder space this is shown to be consistent. The definition is motivated by the…

Analysis of PDEs · Mathematics 2007-05-23 Guenther Hoermann

Applying machine learning to biological sequences - DNA, RNA and protein - has enormous potential to advance human health, environmental sustainability, and fundamental biological understanding. However, many existing machine learning…

Machine Learning · Statistics 2023-04-11 Alan Nawzad Amin , Eli Nathan Weinstein , Debora Susan Marks

We study kernel functions, and associated reproducing kernel Hilbert spaces $\mathscr{H}$ over infinite, discrete and countable sets $V$. Numerical analysis builds discrete models (e.g., finite element) for the purpose of finding…

Functional Analysis · Mathematics 2015-08-17 Palle Jorgensen , Feng Tian

In this paper we provide sufficient conditions for maps of vector bundles on smooth projective varieties to be uniquely determined by their degeneracy schemes. We then specialize to holomorphic distributions and foliations. In particular,…

Algebraic Geometry · Mathematics 2018-10-15 Carolina Araujo , Maurício Corrêa

In this paper we propose a family of tractable kernels that is dense in the family of bounded positive semi-definite functions (i.e. can approximate any bounded kernel with arbitrary precision). We start by discussing the case of stationary…

Machine Learning · Statistics 2015-10-13 Yves-Laurent Kom Samo , Stephen Roberts

In the current work, we study the eigenvalue distribution results of a class of non-normal matrix-sequences which may be viewed as a low rank perturbation, depending on a parameter $\beta>1$, of the basic Toeplitz matrix-sequence…

Numerical Analysis · Mathematics 2024-02-08 Alec Schiavoni Piazza , David Meadon , Stefano Serra-Capizzano

In order to provide a local description of a regular function in a small neighbourhood of a point $x$, it is sufficient by Taylor's theorem to know the value of the function as well as all of its derivatives up to the required order at the…

Functional Analysis · Mathematics 2018-04-12 Sebastian Hensel , Tommaso Rosati

The main purpose of this paper is providing a systematic study and classification of non-scalar kernels for Reproducing Kernel Hilbert Spaces (RKHS), to be used in the analysis of deformation in shape spaces endowed with metrics induced by…

Functional Analysis · Mathematics 2013-09-04 Mario Micheli , Joan Alexis Glaunès