learning, kernel machines are a class of algorithms for pattern analysis, whose best known member is the support-vector machine (SVM). These methods involve...

learning, the radial basis function kernel, or RBF kernel, is a popular kernel function used in various kernelized learning algorithms. In particular,...

The term kernel is used in statistical analysis to refer to a window function. The term "kernel" has several distinct meanings in different branches of...

Compute kernel, in GPGPU programming Kernel method, in machine learning Kernelization, a technique for designing efficient algorithms Kernel, a routine...

are essential tools in the application of kernel methods to large-scale learning problems. Kernel methods (for instance, support vector machines or Gaussian...

statistics, kernel density estimation (KDE) is the application of kernel smoothing for probability density estimation, i.e., a non-parametric method to estimate...

that the kernel method could essentially replace the Volterra series representation, although noting that the latter is more intuitive. This method was developed...

provided by each other, kernels must also provide running programs with a method to make requests to access these facilities. The kernel is also responsible...

It allows ANNs to be studied using theoretical tools from kernel methods. In general, a kernel is a positive-semidefinite symmetric function of two inputs...

In operator theory, a branch of mathematics, a positive-definite kernel is a generalization of a positive-definite function or a positive-definite matrix...