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Reproducing Kernel Hilbert Spaces in Probability and Statistics

The book covers theoretical questions including the latest extension of the formalism, and computational issues and focuses on some of the;

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An Introduction to the Theory of Reproducing Kernel Hilbert Spaces

Reproducing kernel Hilbert spaces have developed into an important tool in many areas, especially statistics and machine learning, and they;

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Kernel Adaptive Filtering

Reproducing kernel Hilbert spaces is a topic of great current interest for applications in signal processing, communications, and controls;

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Generalized Mercer Kernels and Reproducing Kernel Banach Spaces

kernel Hilbert spaces (RKHSs). A key point is to endow Banach spaces with reproducing kernels such that machine learning in RKBSs can be well;

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Kernel Mean Embedding of Distributions

and statistical inference. The basic idea behind this framework is to map distributions into a reproducing kernel Hilbert space (RKHS;

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Nonlinear Numerical Analysis in Reproducing Kernel Space

the authors originally created and gradually improved. Reproducing kernel space is a special Hilbert space. the authors have been engaged;

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Hilbert Space Methods in Signal Processing

This lively and accessible book describes the theory and applications of Hilbert spaces and also presents the history of the subject to;

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Theory of Reproducing Kernels and Applications

generalized reproducing kernels, generalized delta functions, generalized reproducing kernel Hilbert spaces, andas well, a general integral transform;

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Gaussian Measures in Hilbert Space

At the nexus of probability theory, geometry and statistics, a Gaussian measure is constructed on a Hilbert space in two ways: as a product;

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Linear Processes in Function Spaces

of linear processes in function spaces. Mathematical tools are presented, as well as autoregressive processes in Hilbert and Banach spaces and;

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Hilbert Space Methods In Probability And Statistical Inference

Explains how Hilbert space techniques cross the boundaries into the foundations of probability and statistics. Focuses on the theory;

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Gaussian Hilbert Spaces

. Such random variables have many applications in probability theory, other parts of mathematics, statistics and theoretical physics. The;

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Gaussian Hilbert Spaces

. Such random variables have many applications in probability theory, other parts of mathematics, statistics and theoretical physics. The;

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Integral Transforms, Reproducing Kernels and Their Applications

mappings in the framework of Hilbert spaces containing the natural solutions for Fredholm integral equations of the first kind.;

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Integral Transforms, Reproducing Kernels and Their Applications

mappings in the framework of Hilbert spaces containing the natural solutions for Fredholm integral equations of the first kind.;

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J-Contractive Matrix Valued Functions and Related Topics

associated pairs of inner matrix valued functions and reproducing kernel Hilbert spaces. Special attention is paid to the subclasses of regular and;

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Bitangential Direct and Inverse Problems for Systems of Integral and Differential Equations

functions, reproducing kernel Hilbert spaces of vector valued entire functions (with special attention to two important spaces introduced by L;

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Schur Functions, Operator Colligations, and Reproducing Kernel Pontryagin Spaces

researchers in mathematics and engineering. An introductory chapter contains background material, including reproducing kernal Pontryagin spaces;

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Analytic Hilbert Modules

, rigidity, the equivalence problem, the Arveson modules, extension theory, and reproducing Hilbert spaces on n-dimensional complex space.;

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Stochastic Analysis for Gaussian Random Processes and Fields

properties connecting probabilistic notions. In particular, it studies Gaussian random fields using reproducing kernel Hilbert spaces (RKHSs;

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Stochastic Analysis for Gaussian Random Processes and Fields

properties connecting probabilistic notions. In particular, it studies Gaussian random fields using reproducing kernel Hilbert spaces (RKHSs). The;

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Complex Analysis

of holomorphic functions, the Bergman kernel, and unbounded operators on Hilbert spaces to tackle the theory of several variables, in particular the;

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Encyclopedia of Mathematics and its Applications

kernel Hilbert spaces; cylindrical Levy processes are constructed in terms of Poisson random measures; stochastic integrals are introduced;

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Advances in Inequalities of the Schwarz, Gruss & Bessel Type in Inner Product Spaces

The theory of Hilbert spaces plays a central role in contemporary mathematics with numerous applications for Linear Operators, Partial;

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Recent Advances in Operator Theory

Applications held in Groningen, the Netherlands, from June 30-July 3, 1998. The topics include dilation and interpolation problems, reproducing kernel;

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An Invitation to Statistics in Wasserstein Space

This open access book presents the key aspects of statistics in Wasserstein spaces, i.e. statistics in the space of probability measures;

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Digital Nets and Sequences

Hilbert spaces and weighted integration, duality theory for digital nets, polynomial lattice rules, the newest constructions by Niederreiter and;

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