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The modified zeta functions $\sum_{n \in K} n^{-s}$, where $K \subset \N$, converge absolutely for $\Re s > 1/2$. These generalise the Riemann zeta function which is known to have a meromorphic continuation to all of $\C$ with a single pole…

Classical Analysis and ODEs · Mathematics 2009-09-15 Jan-Fredrik Olsen

We consider positive semidefinite kernels valued in the $*$-algebra of adjointable operators on a VE-space (Vector Euclidean space) and that are invariant under actions of $*$-semigroups. A rather general dilation theorem is stated and…

Functional Analysis · Mathematics 2017-02-06 Serdar Ay , Aurelian Gheondea

A space-filling function is a bijection from the unit line segment to the unit square, cube, or hypercube. The function from the unit line segment is continuous. The inverse function, while well-defined, is not continuous. Space-filling…

Computational Geometry · Computer Science 2015-04-21 Aubrey Jaffer

The heat kernel expansion on even-dimensional hyperbolic spaces is asymptotic at both short and long times, with interestingly different Borel properties for these short and long time expansions. Resummations in terms of incomplete gamma…

High Energy Physics - Theory · Physics 2023-05-31 Gerald V. Dunne

We consider mainly the Hilbert space of bianalytic functions on a given domain in the plane, square integrable with respect to a weight. We show how to obtain the asymptotic expansion of the corresponding bianalytic Bergman kernel for power…

Complex Variables · Mathematics 2015-09-23 Haakan Hedenmalm , Antti Haimi

This paper considers different facets of the interplay between reproducing kernel Hilbert spaces (RKHS) and stable analysis/synthesis processes: First, we analyze the structure of the reproducing kernel of a RKHS using frames and…

Functional Analysis · Mathematics 2019-04-02 Michael Speckbacher , Peter Balazs

This work provides theoretical foundations for kernel methods in the hyperspherical context. Specifically, we characterise the native spaces (reproducing kernel Hilbert spaces) and the Sobolev spaces associated with kernels defined over…

Machine Learning · Statistics 2022-11-18 Simon Hubbert , Emilio Porcu , Chris. J. Oates , Mark Girolami

We study algebras of bounded noncommutative (nc) functions on unit balls of operator spaces (nc operator balls) and on their subvarieties. Considering the example of the nc unit polydisk we show that these algebras, while having a natural…

Operator Algebras · Mathematics 2025-04-15 Jeet Sampat , Orr Shalit

Mean-field control problems have received continuous interest over the last decade. Despite being more intricate than in classical optimal control, the linear-quadratic setting can still be tackled through Riccati equations. Remarkably, we…

Optimization and Control · Mathematics 2023-08-23 Pierre-Cyril Aubin-Frankowski , Alain Bensoussan

Recent cosmological observations have achieved high-precision measurements of the Universe's expansion history, prompting the use of nonparametric methods such as Gaussian processes (GP) regression. We apply GP regression for reconstructing…

Cosmology and Nongalactic Astrophysics · Physics 2025-11-21 Jia-yan Jiang , Kang Jiao , Tong-Jie Zhang

We study two extension problems, and their interconnections: (i) extension of positive definite (p.d.) continuous functions defined on subsets in locally compact groups $G$; and (ii) (in case of Lie groups $G$) representations of the…

Functional Analysis · Mathematics 2014-01-22 Palle Jorgensen , Steen Pedersen , Feng Tian

With view to applications in stochastic analysis and geometry, we introduce a new correspondence for positive definite kernels (p.d.) $K$ and their associated reproducing kernel Hilbert spaces. With this we establish two kinds of…

Functional Analysis · Mathematics 2019-11-28 Palle Jorgensen , Feng Tian

This article develops direct and inverse estimates for certain finite dimensional spaces arising in kernel approximation. Both the direct and inverse estimates are based on approximation spaces spanned by local Lagrange functions which are…

Numerical Analysis · Mathematics 2017-09-08 Thomas Hangelbroek , Francis J. Narcowich , Christian Rieger , Joseph D. Ward

This paper generalizes regularized regression problems in a hyper-reproducing kernel Hilbert space (hyper-RKHS), illustrates its utility for kernel learning and out-of-sample extensions, and proves asymptotic convergence results for the…

Machine Learning · Computer Science 2022-10-20 Fanghui Liu , Lei Shi , Xiaolin Huang , Jie Yang , Johan A. K. Suykens

Asymptotic expansions as well as necessary and sufficient conditions are provided for the pointwise convergence of the spherical partial integrals of the associated Fourier transforms on the real hyperbolic space. The proposed method…

Mathematical Physics · Physics 2020-05-25 Agapitos N. Hatzinikitas

Foundations of the theory of Hilbert spaces with reproducing kernels are discussed. It is demonstrated that the claims in the papers of S.Saitoh and in his book "Theory of reproducing kernels and applications, Pitman research notes, 189,…

Mathematical Physics · Physics 2007-05-23 A. G. Ramm

We introduce a Cherednik kernel and a hypergeometric function for integral root systems and prove their relation to spherical functions associated with Riemannian symmetric spaces of reductive Lie groups. Furthermore, we characterize the…

Classical Analysis and ODEs · Mathematics 2024-10-10 Dominik Brennecken

Highly oscillatory integrals, such as those involving Bessel functions, are best evaluated analytically as much as possible, as numerical errors can be difficult to control. We investigate indefinite integrals involving monomials in $x$…

Classical Analysis and ODEs · Mathematics 2017-03-21 Jolyon K. Bloomfield , Stephen H. P. Face , Zander Moss

In a previous work, we developed an algorithm for the computation of incomplete Bessel functions, which pose as a numerical challenge, based on the $G_{n}^{(1)}$ transformation and Slevinsky-Safouhi formula for differentiation. In the…

Numerical Analysis · Mathematics 2022-04-26 Richard M. Slevinsky , Hassan Safouhi

We describe a method to perform functional operations on probability distributions of random variables. The method uses reproducing kernel Hilbert space representations of probability distributions, and it is applicable to all operations…

Machine Learning · Statistics 2016-09-14 Bernhard Schölkopf , Krikamol Muandet , Kenji Fukumizu , Jonas Peters