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A survey of kernel and spectral methods for clustering [PDF]
, 2007 Clustering algorithms are a useful tool to explore data structures and have been employed in many disciplines. The focus of this paper is the partitioning clustering problem with a special interest in two recent approaches: kernel and spectral methods ...
Masulli, F. +11 more
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Analytic Kramer kernels, Lagrange-type interpolation series and de Branges spaces [PDF]
, 2011 The classical Kramer sampling theorem provides a method for obtaining orthogonal sampling formulas. In particular, when the involved kernel is analytic in the sampling parameter it can be stated in an abstract setting of reproducing kernel Hilbert spaces
Hernández-Medina, Miguel A. +7 more
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Approximate solution of nonlinear multi-point boundary value problem on the half-line
Mathematical Modelling and Analysis, 2012 In this work, we construct a novel weighted reproducing kernel space and give the expression of reproducing kernel function skillfully. Based on the orthogonal basis established in the reproducing kernel space, an efficient algorithm is provided to solve
Jing Niu, Ying Zhen Lin, Chi Ping Zhang
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Interpreting the dual Riccati equation through the LQ reproducing kernel
Comptes Rendus. Mathématique, 2021 In this study, we provide an interpretation of the dual differential Riccati equation of Linear-Quadratic (LQ) optimal control problems. Adopting a novel viewpoint, we show that LQ optimal control can be seen as a regression problem over the space of ...
Aubin-Frankowski, Pierre-Cyril
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Metamorphosis of images in reproducing kernel Hilbert spaces [PDF]
Advances in Computational Mathematics, 2015 Metamorphosis is a method for diffeomorphic matching of shapes, with many potential applications for anatomical shape comparison in medical imagery, a problem which is central to the field of computational anatomy. An important tool for the practical application of metamorphosis is a numerical method based on shooting from the initial momentum, as this
Casey L. Richardson, Laurent Younes
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Abstract and Applied Analysis, 2013 A new analytical method for the computation of reproducing kernel is proposed and tested on some examples. The expression of reproducing kernel on infinite interval is obtained concisely in polynomial form for the first time. Furthermore, as a particular
Jing Niu, Yingzhen Lin, Minggen Cui
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Alexandria Engineering Journal, 2020 In this paper, on the basis of the reproducing kernel functions, a novel meshless algorithm is explored for fractional advection–diffusion-reaction equations (ADREs) with Caputo time variable order.
Xiuying Li, Boying Wu
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New reproducing kernel functions in the reproducing kernel Sobolev spaces
AIMS Mathematics, 2020 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Akgul, Ali +2 more
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Reproducing kernel Banach spaces for machine learning [PDF]
2009 International Joint Conference on Neural Networks, 2009 Reproducing kernel Hilbert space (RKHS) methods have become powerful tools in machine learning. However, their kernels, which measure similarity of inputs, are required to be symmetric, constraining certain applications in practice. Furthermore, the celebrated representer theorem only applies to regularizers induced by the norm of an RKHS.
Haizhang Zhang +2 more
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Reproducing Kernel in Krein Spaces
WSEAS TRANSACTIONS ON MATHEMATICS, 2022 This article describes a new form to introduce a reproducing kernel for a Krein space based on orthogonal projectors enabling to describe the kernel of a Krein space as the difference between the kernel of definite positive subspace and the kernel of definite negative subspace corresponding to kernel of the associated Hilbert space. As application, the
Osmin Ferrer +2 more
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