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Related papers: Complete Nevanlinna-Pick kernels

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Volterra series are especially useful for nonlinear system identification, also thanks to their capability to approximate a broad range of input-output maps. However, their identification from a finite set of data is hard, due to the curse…

Machine Learning · Computer Science 2019-11-13 Alberto Dalla Libera , Ruggero Carli , Gianluigi Pillonetto

Nevanlinna's five-value theorem is well-known as a famous theorem in value distribution theory, which asserts that two non-constant meromorphic functions on $\mathbb C$ are identical if they share five distinct values ignoring…

Complex Variables · Mathematics 2023-09-01 Xianjing Dong

In this paper, we study when the kernel of a complete hereditary cotorsion pair is the additive closure of a tilting module. Applications go in three directions. The first is to characterize when the little finitistic dimension is finite.…

Rings and Algebras · Mathematics 2019-05-17 Jian Wang , Yunxia Li , Jiangsheng Hu

In this paper, we give a new approach to the theory of strictly positive kernels. Our method is based on the structure of Fock spaces. As its applications, various examples of strictly positive kernels are given. Moreover, we give a new…

Functional Analysis · Mathematics 2022-09-28 Michio Seto

Hilbertian kernel methods and their positive semidefinite kernels have been extensively used in various fields of applied mathematics and machine learning, owing to their several equivalent characterizations. We here unveil an analogy with…

Functional Analysis · Mathematics 2023-01-10 Pierre-Cyril Aubin-Frankowski , Stéphane Gaubert

The Lyapunov order appeared in the study of Nevanlinna-Pick interpolation for positive real odd functions with general (real) matrix points. For real or complex matrices $A$ and $B$ it is said that $B$ Lyapunov dominates $A$ if…

Functional Analysis · Mathematics 2021-11-18 Sanne ter Horst , Alma van der Merwe

This paper presents an algorithm, Voted Kernel Regularization , that provides the flexibility of using potentially very complex kernel functions such as predictors based on much higher-degree polynomial kernels, while benefitting from…

Machine Learning · Computer Science 2015-09-16 Corinna Cortes , Prasoon Goyal , Vitaly Kuznetsov , Mehryar Mohri

We present a new formula of Cauchy type for the nonsymmetric Macdonald polynomials which are joint eigenfunctions of q-Dunkl operators. This gives the explicit formula for a reproducing kernel on the polynomial ring of n variables.

q-alg · Mathematics 2008-02-03 K. Mimachi , M. Noumi

We extend the study of the Pick class, the set of complex analytic functions taking the upper half plane into itself, to the noncommutative setting. R. Nevanlinna showed that elements of the Pick class have certain integral representations…

Functional Analysis · Mathematics 2013-10-18 J. E. Pascoe , Ryan Tully-Doyle

We analyse a special case of the robust stabilization problem under structured uncertainty. We obtain a new criterion for the solvability of the spectral Nevanlinna-Pick problem, which is a special case of the $\mu$-synthesis problem of…

Complex Variables · Mathematics 2013-03-22 Jim Agler , Z. A. Lykova , N. J. Young

A linear system on a smooth complex algebraic surface gives rise to a family of smooth curves in the surface. Such a family has a topological monodromy representation valued in the mapping class group of a fiber. Extending arguments of…

Algebraic Geometry · Mathematics 2024-10-08 Nick Salter

The paper introduces new sufficient conditions of strict positive definiteness for kernels on d-dimensional spheres which are not radially symmetric but possess specific coefficient structures. The results use the series expansion of the…

Numerical Analysis · Mathematics 2021-05-07 Martin Buhmann , Janin Jäger

Kernel matrices are a key quantity in kernel-based approximation, and important properties such as stability and algorithmic convergence can be analyzed with their help. In this work we refine a multivariate Ingham-type theorem, which is…

Numerical Analysis · Mathematics 2025-07-28 Tizan Wenzel , Armin Iske

We consider the kernel completion problem with the presence of multiple views in the data. In this context the data samples can be fully missing in some views, creating missing columns and rows to the kernel matrices that are calculated…

Machine Learning · Computer Science 2022-06-01 Riikka Huusari , Cécile Capponi , Paul Villoutreix , Hachem Kadri

Models like support vector machines or Gaussian process regression often require positive semi-definite kernels. These kernels may be based on distance functions. While definiteness is proven for common distances and kernels, a proof for a…

Machine Learning · Computer Science 2018-07-11 Martin Zaefferer , Thomas Bartz-Beielstein , Günter Rudolph

We show that kernel-based quadrature rules for computing integrals can be seen as a special case of random feature expansions for positive definite kernels, for a particular decomposition that always exists for such kernels. We provide a…

Machine Learning · Computer Science 2015-11-10 Francis Bach

We consider weakly positive semidefinite kernels valued in ordered $*$-spaces with or without certain topological properties, and investigate their linearisations (Kolmogorov decompositions) as well as their reproducing kernel spaces. The…

Functional Analysis · Mathematics 2025-11-04 Serdar Ay , Aurelian Gheondea

We propose a new approach to the value distribution theory of entire holomorphic curves. We define a ``packing density'' of an entire holomorphic curve, and show that it has various non-trivial properties. We prove a ``gap theorem'' for…

Complex Variables · Mathematics 2007-05-23 Masaki Tsukamoto

We use the kernel category to give a finiteness condition for semigroups. As a consequence we provide yet another proof that finitely generated periodic semigroups of matrices are finite.

Group Theory · Mathematics 2019-08-15 Benjamin Steinberg

The paper introduces a new characterisation of strictly positive definiteness for kernels on the 2-sphere without assuming the kernel to be radially (isotropic) or axially symmetric. The results use the series expansion of the kernel in…

Numerical Analysis · Mathematics 2022-05-06 Janin Jäger