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The default kernel is located in the file /kernel.
Although here we only use the default kernel, the possibility of modifying the kernel leaves room for performance improvement.
By default, kernel launches and calls to the CUDA runtime API for transferring memory occur on what is known as the default stream and subsequently execute in order.
In this work, the default kernel is the Gaussian kernel, κ x,x ′)= exp(−||x−x ′||2/2σ 2), where σ is the kernel size.
In all the experents carried out, the radial basis function is used as the default kernel function.
We used the default kernel and default bandwidth functions implemented in R. We thank M. Reinikainen from the Tvärminne Zoological Station and J. Järvinen from the Finnish Meteorological Institute for the weather data and discussions; T. Zumbrunn for discussion, help during the preparation of the raw data and collection of evaporation data.
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Our simulation results show that the lifting based kernels, generated from the proposed system, are capable of achieving superior compression performance compared to the default kernels adopted in the JPEG2000 standard (at a classification rate of 70%).
This makes methods that treat the input data as static, such as support vector machines (SVM) with default kernels, less appropriate for this task.
Non-default kernels for GP were introduced in the caret framework by in-house R scripts and by the definition of custom models (custom option in the caret package) implementing kernel functions from either the kernlab[57] package or in-house kernel functions.
We used an SVM with a default polynomial kernel.
We used the default linear kernel for the SVM classifier.
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