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Devoted to multi-task learning and structured output learning, operator-valued kernels provide a flexible tool to build vector-valued functions in the context of Reproducing Kernel Hilbert Spaces. To scale up these methods, we extend the…

Machine Learning · Computer Science 2018-05-25 Romain Brault , Florence d'Alché-Buc , Markus Heinonen

We introduce a notion of a noncommutative function defined on a domain of $d$-tuples of bounded operators on an infinite dimensional Hilbert space. Inverse and implicit function theorems in this setting are established. When these…

Functional Analysis · Mathematics 2021-08-25 Mark E. Mancuso

In this paper we investigate the reproducing kernel Hilbert space where the polylogarithm appears as kernel functions. This investigation begins with the properties of functions in this space, and here a connection to the classical Hardy…

Functional Analysis · Mathematics 2015-03-06 Joel A. Rosenfeld

In this paper we define an internal binary operation between functions called in the text \emph{fractal convolution}, that applies a pair of mappings into a fractal function. This is done by means of a suitable Iterated Function System. We…

Classical Analysis and ODEs · Mathematics 2019-07-16 M. A. Navascués , P. Massopust

In this article we consider the classical singular integral operator over a local field with rough kernels. We study the boundedness of such an operator on different function spaces by relaxing the smoothness condition on kernels.

Functional Analysis · Mathematics 2022-04-07 Salman Ashraf , Qaiser Jahan

We undertake a reconstruction of the epistemic significance of research on operational theories in quantum foundations. We suggest that the space of operational theories is analogous to the space of possible worlds employed in the possible…

History and Philosophy of Physics · Physics 2022-01-25 Emily Adlam

In this paper, we study uniqueness problems for an entire function that shares small functions of finite order with their difference operators. In particular, we give a generalization of results in [2,3,13].

Complex Variables · Mathematics 2015-07-31 Abdallah El Farissi , Zinelâabidine Latreuch , Benharrat Belaïdi , Asim Asiri

Many machine learning algorithms can be interpreted as procedures for estimating functions defined on the data distribution. In this paper we present a conceptual framework that formulates a wide range of learning problems as variational…

Machine Learning · Computer Science 2026-03-17 K. Lakshmanan

We define the notion of an invariant function on a cluster ensemble with respect to an action of the cluster modular group on its associated function fields. We realize many examples of previously studied functions as elements of this type…

Commutative Algebra · Mathematics 2024-01-08 Dani Kaufman

The purpose of this paper is to give an overview of the operator structure of frames, where the operator belongs to certain classes of linear operators and the element belongs to $H$. We discuss the size of the set of such elements. Also,…

Functional Analysis · Mathematics 2022-12-06 Jahangir Cheshmavar , Ayyaneh Dallaki

The present report, has been inspired by the need of the author and its colleagues to understand the underlying theory of Wirtinger's Calculus and to further extend it to include the kernel case. The aim of the present manuscript is…

Machine Learning · Computer Science 2010-06-02 P. Bouboulis

We discuss various theorems about bounded analytic functions on the bidisk that were proved using operator theory.

Complex Variables · Mathematics 2009-01-08 Jim Agler , John McCarthy

In this work, we define a new class of fractional analytic functions containing functional parameters in the open unit disk. By employing this class, we introduce two types of fractional operators, differential and integral. The fractional…

Functional Analysis · Mathematics 2016-01-14 Rabha W. Ibrahim , Adem Kilicman , Zainab E. Abdulnaby

We use a classical characterisation to prove that functions which are bounded away from zero cannot be elements of reproducing kernel Hilbert spaces whose reproducing kernels decays to zero in a suitable way. The result is used to study…

Functional Analysis · Mathematics 2021-02-23 Toni Karvonen

Deep kernel learning refers to a Gaussian process that incorporates neural networks to improve the modelling of complex functions. We present a method that makes this approach feasible for problems where the data consists of line integral…

Machine Learning · Statistics 2019-09-05 Carl Jidling , Johannes Hendriks , Thomas B. Schön , Adrian Wills

An operatorial method, already employed to formulate a generalization of the Ramanujan master theorem, is applied to the evaluation of integrals of various type. This technique provide a very flexible and powerful tool yielding new results…

Classical Analysis and ODEs · Mathematics 2012-11-07 D. Babusci , G. Dattoli , G. H. E. Duchamp , K. Górska , K. A. Penson

We review the basic properties of paired operators and their adjoints, the transposed paired operators, with particular reference to commutation relations, and we study the properties of their kernels, bringing out their similarities and…

Functional Analysis · Mathematics 2024-12-23 M. Cristina Câmara , Jonathan R. Partington

Reproducing kernel Hilbert spaces are elucidated without assuming prior familiarity with Hilbert spaces. Compared with extant pedagogic material, greater care is placed on motivating the definition of reproducing kernel Hilbert spaces and…

History and Overview · Mathematics 2015-11-06 Jonathan H. Manton , Pierre-Olivier Amblard

We introduce the notion of rationality for hyperholomorphic functions (functions in the kernel of the Cauchy-Fueter operator). Following the case of one complex variable, we give three equivalent definitions: the first in terms of…

Functional Analysis · Mathematics 2007-05-23 D. Alpay , M. Shapiro , D. Volok

In this paper, we concern the kernel of linear operator for a class of Grushin equation. First, we study the kernel space of linear operator for a general Grushin equation. Then, we provide an exact expression for the kernel space of linear…

Analysis of PDEs · Mathematics 2024-09-17 Yawei Wei , Xiaodong Zhou
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