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We tackle the problem of optimizing over all possible positive definite radial kernels on Riemannian manifolds for classification. Kernel methods on Riemannian manifolds have recently become increasingly popular in computer vision. However,…

Computer Vision and Pattern Recognition · Computer Science 2014-12-16 Sadeep Jayasumana , Richard Hartley , Mathieu Salzmann , Hongdong Li , Mehrtash Harandi

This note presents an elementary iterative construction of the generators for the complex $K$-groups $K_i(C(\SM^d))$ of the $d$-dimensional spheres. These generators are explicitly given as the restrictions of Dirac or Weyl Hamiltonians to…

Mathematical Physics · Physics 2024-03-29 Hermann Schulz-Baldes , Tom Stoiber

Existence and uniqueness of solutions for nonlocal Cahn-Hilliard equations with degenerate potential is shown. The nonlocality is described by means of a symmetric singular kernel not falling within the framework of any previous existence…

Analysis of PDEs · Mathematics 2020-12-11 Elisa Davoli , Helene Ranetbauer , Luca Scarpa , Lara Trussardi

In this paper a local approximation method on the sphere is presented. As interpolation scheme we consider a partition of unity method, such as the modified spherical Shepard's method, which uses zonal basis functions (ZBFs) plus spherical…

Numerical Analysis · Mathematics 2014-04-08 Alessandra De Rossi

Solution of some boundary value problems and initial problems in unique ball leads to the convergence and sumability problems of Fourier series of given function by eigenfunctions of Laplace operator on a sphere - spherical harmonics. Such…

Spectral Theory · Mathematics 2009-03-02 Abdumalik A. Rakhimov

This paper is concerned with the location of nodal sets of eigenfunctions of the Dirichlet Laplacian in thin tubular neighbourhoods of hypersurfaces of the Euclidean space of arbitrary dimension. In the limit when the radius of the…

Analysis of PDEs · Mathematics 2015-04-27 David Krejcirik , Matej Tusek

We give theorems that can be used to upper bound the densities of packings of different spherical caps in the unit sphere and of translates of different convex bodies in Euclidean space. These theorems extend the linear programming bounds…

Metric Geometry · Mathematics 2014-09-26 David de Laat , Fernando Mario de Oliveira Filho , Frank Vallentin

We consider the minimal energy problem on the unit sphere $\mathbb S^2$ in the Euclidean space $\mathbb R^3$ immersed in an external field $Q$, where the charges are assumed to interact via Newtonian potential $1/r$, $r$ being the Euclidean…

Classical Analysis and ODEs · Mathematics 2015-10-23 Mykhailo Bilogliadov

Kernelization algorithms are polynomial-time reductions from a problem to itself that guarantee their output to have a size not exceeding some bound. For example, d-Set Matching for integers d>2 is the problem of finding a matching of size…

Data Structures and Algorithms · Computer Science 2018-12-10 Holger Dell , Dániel Marx

Many results in mass partitions are proved by lifting $\mathbb{R}^d$ to a higher-dimensional space and dividing the higher-dimensional space into pieces. We extend such methods to use lifting arguments to polyhedral surfaces. Among other…

Combinatorics · Mathematics 2021-09-09 Pablo Soberón , Yuki Takahashi

In this paper we investigate and compare different gradient algorithms designed for the domain expression of the shape derivative. Our main focus is to examine the usefulness of kernel reproducing Hilbert spaces for PDE constrained shape…

Optimization and Control · Mathematics 2016-04-20 Martin Eigel , Kevin Sturm

A strengthened canonical quantization scheme for the constrained motion on a curved hypersurface is proposed with introduction of the second category of fundamental commutation relations between Hamiltonian and positions/momenta, whereas…

Quantum Physics · Physics 2014-10-07 Q. H. Liu

There exists a plethora of parametric models for positive definite kernels, and their use is ubiquitous in disciplines as diverse as statistics, machine learning, numerical analysis, and approximation theory. Usually, the kernel parameters…

Machine Learning · Statistics 2025-01-06 Xavier Emery , Emilio Porcu , Moreno Bevilacqua

The seminal theorem of I.J. Schoenberg characterizes positive definite (p.d.) kernels on the unit sphere $S^{n-1}$ invariant under the automorphisms of the sphere. We obtain two generalizations of this theorem for p.d. kernels on fiber…

Classical Analysis and ODEs · Mathematics 2019-04-05 Olga Kuryatnikova , Juan C. Vera

The corona problem was motivated by the question of the density of the open unit disk D in the maximal ideal space of the algebra, H1(D), of bounded holomorphic functions on D. In this note we study relationships of the problem with…

Functional Analysis · Mathematics 2012-12-04 Ronald G. Douglas

In this paper, we study punctured spheres in two dimensional ball quotient compactifications $(X, D)$. For example, we show that smooth toroidal compactifications of ball quotients cannot contain properly holomorphically embedded…

Geometric Topology · Mathematics 2018-06-28 Luca F. Di Cerbo , Matthew Stover

We introduce a class of iterated integrals, defined through a set of linearly independent integration kernels on elliptic curves. As a direct generalisation of multiple polylogarithms, we construct our set of integration kernels ensuring…

High Energy Physics - Theory · Physics 2018-06-13 Johannes Broedel , Claude Duhr , Falko Dulat , Lorenzo Tancredi

In this paper, a class of high order numerical schemes is proposed to solve the nonlinear parabolic equations with variable coefficients. This method is based on our previous work [10] for convection-diffusion equations, which relies on a…

Numerical Analysis · Mathematics 2020-12-30 Kaipeng Wang , Andrew Christlieb , Yan Jiang , Mengping Zhang

In the framework of Clifford analysis, a chain of harmonic and monogenic potentials is constructed in the upper half of Euclidean space $\mR^{m+1}$, including a higher dimensional generalization of the complex logarithmic function. Their…

Classical Analysis and ODEs · Mathematics 2012-10-09 Fred Brackx , Hendrik De Bie , Hennie De Schepper

We present a data-driven method for computing approximate forward reachable sets using separating kernels in a reproducing kernel Hilbert space. We frame the problem as a support estimation problem, and learn a classifier of the support as…

Optimization and Control · Mathematics 2020-11-20 Adam J. Thorpe , Kendric R. Ortiz , Meeko M. K. Oishi