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Reproducing Kernel Hilbert Spaces and Discrimination
2015In this chapter, it is examined to what extent RKHS’s allow one to discriminate between probability laws, that is determine their equivalence or singularity.
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Sampling in Reproducing Kernel Hilbert Space
2014An account of sampling in the setting of reproducing kernel spaces is given, the main point of which is to show that the sampling theory of Kluvanek, even though it is very general in some respects, is nevertheless a special case of the reproducing kernel theory. A Dictionary is provided as a handy summary of the essential steps.
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Relations Between Reproducing Kernel Hilbert Spaces
2015When one claims that the signal must be in the RKHS of the noise, for detection to be nonsingular, one in fact means that the family of its paths should be contained, as a set, in the RKHS of that noise. One shall see in the next chapter that such a requirement entails a specific inclusion of related RKHS’s, and the entire topic may be seen as a ...
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Reproducing Kernel Hilbert Spaces: The Rudiments
2015This chapter provides and illustrates, following the table of contents, the basic tools of the theory of reproducing kernel Hilbert spaces.
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Contrastive Multi-View Kernel Learning
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023Jiyuan Liu, Xinwang Liu, Yuanqing Xia
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Simultaneous Global and Local Graph Structure Preserving for Multiple Kernel Clustering
IEEE Transactions on Neural Networks and Learning Systems, 2021Zhenwen Ren, Quansen Sun
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Rainfall-runoff modeling through regression in the reproducing kernel Hilbert space algorithm
Journal of Hydrology, 2020Mir Jafar Sadegh Safari +1 more
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Kernels and Reproducing Kernel Hilbert Spaces
2008Ingo Steinwart, Andreas Christmann
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