Results 71 to 80 of about 1,777,436 (249)
The Convergence Rate for a K-Functional in Learning Theory
Journal of Inequalities and Applications, 2010 It is known that in the field of learning theory based on reproducing kernel Hilbert spaces the upper bounds estimate for a K-functional is needed.
Bao-Huai Sheng, Dao-Hong Xiang
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On the stability test for reproducing kernel Hilbert spaces
CoRR, 2023 Reproducing kernel Hilbert spaces (RKHSs) are special Hilbert spaces where all the evaluation functionals are linear and bounded. They are in one-to-one correspondence with positive definite maps called kernels. Stable RKHSs enjoy the additional property of containing only functions and absolutely integrable.
Mauro Bisiacco, Gianluigi Pillonetto
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Magnetic Resonance in Medicine, EarlyView.ABSTRACT Purpose To develop and validate a repeatable and reproducible approach, QuantoRAGE, for simultaneous whole‐brain T1 and T2 mapping using adiabatic magnetization preparation. Methods QuantoRAGE is a 3D FLASH‐based sequence using an adiabatic T2‐prepared inversion followed by two readout blocks.
Natalia Pato Montemayor +21 more
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Approximation properties for multiplier algebras of reproducing kernel Hilbert spaces [PDF]
, 2008 In this note, it is proved that multiplier algebras of analytic reproducing kernel Hilbert spaces which are compatible with the action of the torus group possess Kraus’ completely contractive approximation property (CCAP) and, consequently, have the ...
Barbian, Christoph, Barbian Christoph
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Error Bound of Mode-Based Additive Models
Entropy, 2021 Due to their flexibility and interpretability, additive models are powerful tools for high-dimensional mean regression and variable selection. However, the least-squares loss-based mean regression models suffer from sensitivity to non-Gaussian noises ...
Hao Deng +3 more
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Vector valued reproducing kernel Hilbert spaces and universality [PDF]
, 2008 This paper is devoted to the study of vector valued reproducing kernel Hilbert spaces. We focus on two aspects: vector valued feature maps and universal kernels.
C. Carmeli +3 more
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Singular Value Decomposition of Operators on Reproducing Kernel Hilbert Spaces [PDF]
Advances in Dynamics, Optimization and Computation, 2018 Reproducing kernel Hilbert spaces (RKHSs) play an important role in many statistics and machine learning applications ranging from support vector machines to Gaussian processes and kernel embeddings of distributions.
Mattes Mollenhauer +3 more
semanticscholar +1 more source
n-Best kernel approximation in reproducing kernel Hilbert spaces
Applied and Computational Harmonic Analysis, 2022 By making a seminal use of the maximum modulus principle of holomorphic functions we prove existence of $n$-best kernel approximation for a wide class of reproducing kernel Hilbert spaces of holomorphic functions in the unit disc, and for the corresponding class of Bochner type spaces of stochastic processes.
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Privacy‐Preserving Data‐Driven Distributed MPC for Heterogeneous Nonlinear Multi‐Agent Systems
International Journal of Robust and Nonlinear Control, EarlyView.ABSTRACT Distributed model predictive control (DMPC) is a cornerstone for coordinating multi‐agent systems, yet simultaneously ensuring data privacy, handling unknown nonlinear dynamics, and managing heterogeneous constraints remains an open challenge.
Mahmood Mazare, Hossein Ramezani
wiley +1 more source
Reproducing kernel Hilbert spaces [PDF]
, 2005 Cataloged from PDF version of article.In this thesis we make a survey of the theory of reproducing kernel Hilbert spaces associated with positive definite kernels and we illustrate their applications for interpolation problems of Nevanlinna-Pick type ...
Okutmuştur, Baver
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