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In this paper, we describe families of those bounded linear operators on a separable Hilbert space that are simultaneously unitarily equivalent to integral operators on $L_2(R)$ with bounded and arbitrarily smooth Carleman kernels. The main…

Spectral Theory · Mathematics 2007-05-23 Igor M. Novitskii

We start by showing how to approximate unitary and bounded self-adjoint operators by operators in finite dimensional spaces. Using ultraproducts we give a precise meaning for the approximation. In this process we see how the spectral…

Logic · Mathematics 2022-08-16 Åsa Hirvonen , Tapani Hyttinen

Kernel mean embeddings have recently attracted the attention of the machine learning community. They map measures $\mu$ from some set $M$ to functions in a reproducing kernel Hilbert space (RKHS) with kernel $k$. The RKHS distance of two…

Machine Learning · Statistics 2019-12-18 Carl-Johann Simon-Gabriel , Bernhard Schölkopf

We study the dominant eigenstructure of positive-kernel Fredholm operators arising in multi-state structured population models, including integral projection models and age-structured McKendrick-type equations. To obtain a determinant-free…

Populations and Evolution · Quantitative Biology 2026-04-28 Ryo Oizumi , Kensaku Kinjo , Yuki Chino

In this work, we investigate the generalization properties of random feature methods. Our analysis extends prior results for Tikhonov regularization to a broad class of spectral regularization techniques and further generalizes the setting…

Machine Learning · Statistics 2026-03-03 Mike Nguyen , Nicole Mücke

Parametric entities appear in many contexts, be it in optimisation, control, modelling of random quantities, or uncertainty quantification. These are all fields where reduced order models (ROMs) have a place to alleviate the computational…

Numerical Analysis · Mathematics 2019-11-25 Hermann G. Matthies , Roger Ohayon

We introduce the concept of completely positive roots of completely positive maps on operator algebras. We do this in different forms: as asymptotic roots, proper discrete roots and as continuous one-parameter semigroups of roots. We…

Operator Algebras · Mathematics 2020-04-21 B. V. Rajarama Bhat , Robin Hillier , Nirupama Mallick , Vijaya Kumar U

Random operator tuples possess a rich second-moment structure that is not visible at the level of pointwise operator inequalities. This paper shows that their averaged word moments form a positive kernel whose behavior is controlled by a…

Functional Analysis · Mathematics 2025-12-12 James Tian

We define an extension of operator-valued positive definite functions from the real or complex setting to topological algebras, and describe their associated reproducing kernel spaces. The case of entire functions is of special interest,…

Functional Analysis · Mathematics 2024-01-05 Daniel Alpay , Ismael L. Paiva

We derive Paschke's GNS construction for completely positive maps on unital pro-C*-algebras from the KSGNS construction, presented by M. Joita [J. London Math. Soc. {\bf 66} (2002), 421--432], and then we deduce an analogue of Stinespring…

Operator Algebras · Mathematics 2017-01-05 Khadijeh Karimi , Kamran Sharifi

A proof using the theory of completely positive maps is given to the fact that if $A \in M_2$, or $A \in M_3$ has a reducing eigenvalue, then every bounded linear operator $B$ with $W(B) \subseteq W(A)$ has a dilation of the form $I \otimes…

Functional Analysis · Mathematics 2019-02-07 Chi-Kwong Li , Yiu-Tung Poon

We study the stability properties of nonlinear multi-task regression in reproducing Hilbert spaces with operator-valued kernels. Such kernels, a.k.a. multi-task kernels, are appropriate for learning prob- lems with nonscalar outputs like…

Machine Learning · Computer Science 2013-06-18 Julien Audiffren , Hachem Kadri

A new method for hierarchical clustering is presented. It combines treelets, a particular multiscale decomposition of data, with a projection on a reproducing kernel Hilbert space. The proposed approach, called kernel treelets (KT),…

Machine Learning · Statistics 2019-07-24 Hedi Xia , Hector D. Ceniceros

The accuracy and complexity of kernel learning algorithms is determined by the set of kernels over which it is able to optimize. An ideal set of kernels should: admit a linear parameterization (tractability); be dense in the set of all…

Machine Learning · Statistics 2020-05-04 Brendon K. Colbert , Matthew M. Peet

We study kernel quadrature rules with convex weights. Our approach combines the spectral properties of the kernel with recombination results about point measures. This results in effective algorithms that construct convex quadrature rules…

Numerical Analysis · Mathematics 2022-10-12 Satoshi Hayakawa , Harald Oberhauser , Terry Lyons

Kernel approximation via nonlinear random feature maps is widely used in speeding up kernel machines. There are two main challenges for the conventional kernel approximation methods. First, before performing kernel approximation, a good…

Machine Learning · Statistics 2015-03-16 Felix X. Yu , Sanjiv Kumar , Henry Rowley , Shih-Fu Chang

In this paper, we study composition operators on Hilbert space of complex-valued harmonic functions. In particular, we explore isometries, the type of self-map that generate bounded composition operator, and characterize the boundedness of…

Functional Analysis · Mathematics 2025-03-14 Tseganesh Getachew Gebrehana , Hunduma Legesse Geleta

In this work, we consider "finite bandwidth" reproducing kernel Hilbert spaces which have orthonormal bases of the form $f_n(z)=z^n \prod_{j=1}^J \left( 1 - a_{n}w_j z \right)$, where $w_1 ,w_2, \ldots w_J $ are distinct points on the…

Functional Analysis · Mathematics 2023-10-18 Gregory T. Adams , Nathan A. Wagner

We extend the recent results concerning boundedness of the maximal regularity operator on tent spaces. This leads us to develop a singular integral operator theory on tent spaces. Such operators have operator-valued kernels. A seemingly…

Classical Analysis and ODEs · Mathematics 2012-03-20 Pascal Auscher , Christoph Kriegler , Sylvie Monniaux , Pierre Portal

Starting from a result of Stewart, Tijdeman and Ruzsa on iterated difference sequences, we introduce the notion of iterated compositions of linear operations. We prove a general result on the stability of such compositions (with bounded…

Number Theory · Mathematics 2010-05-21 Norbert Hegyvári , Francois Hennecart , Alain Plagne
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