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A Kernel Function Method in Clustering
2005Cluster analysis is one of main methods used in data mining. So far there have existed many cluster analysis approaches such as partitioning method, density-based, k-means, k-nearest neighborhood, etc. Recently, some researchers have explored a few kernel-based clustering methods, e.g., kernel-based K-means clustering.
Ling Zhang 0001 +2 more
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DECOMPOSITION OF A CONTINUOUS FUNCTION-KERNEL
Analysis, 1989Let X be a locally compact Hausdorff space with a countable base, and let G be a continuous function-kernel on X that satisfies the domination principle. This paper is concerned with the problem of decomposing G into a sum of two Borel measurable function-kernels in a particular way, and such that one also satisfies the domination principle.
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Kernel Functions Based on Derivation
2009In this paper we explain the fundamental idea of designing a class of kernel functions, called the intentional kernel, for structured data. The intentional kernel is designed with the property that every structured data is defined by derivation. Derivation means transforming a data or an expression into another.
Koichiro Doi, Akihiro Yamamoto
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Kernel Networks for Function Approximation
2016Capabilities of radial convolution kernel networks to approximate multivariate functions are investigated. A necessary condition for universal approximation property of convolution kernel networks is given. Kernels that satisfy the condition in arbitrary dimension are investigated in terms of their Hankel and Fourier transforms. A computational example
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Choice of Kernel Function for Density Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence, 1980Let l=f^n(x) be the kernel estimate of a density f(x) from a sample of size n. Wahba [6] has developed an upper bound to E[f(x)-l=f^n(x)]2. In the present paper, we find the kernel function of finite support [m=-T, T] that minimizes Wahba's upper bound. It is Q(y) = (1 + am=-1) (2T)m=-1 [1-m=-a|y|a] where a = 2-pm=-1, p m=ge 1.
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Major advancements in kernel function approximation
Artificial Intelligence Review, 2020Kumudha Raimond, Deena P. Francis
exaly
Heat kernels and theta functions
1996zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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