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The different constants are also summed in this kernel.
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This paper describes an experience in parallelizing this kernel routine.
We use this kernel in the present work for unsupervised action recognition, whereas in the supervised case we introduce a different characteristic kernel in the following section.
Several simulation studies demonstrated the effectiveness of this kernel in reducing ITs[13, 14, 25, 26].
Therefore, it is not clear whether applying this kernel in Human will be beneficial or not.
We used the freely and publicly available ChemCPP software to compute this kernel in the experiments.
For this kernel, in the absence of covariates, the KBAC score test is given by with significance assessed via permutation.
The kernel is symmetric in, and the value of this kernel for is obtained by interchanging and in (4.25).
In this paper, kernel partial least squares (KPLS) method is modified based on orthogonal independent component analysis (O-ICA).
In this work, kernel partial least squares (PLS) was applied to predict inferentially key process variables in an industrial cokes wastewater treatment plant.
In this work kernel density estimation is used to generate probability density functions ( pdfs ) for bond length, bond angle and torsion angle histograms derived from the CSD.
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