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More specifically, the benchmark measures the performance of Breadth-First Search (BFS), which is utilized as a kernel for important and more complex algorithms such as connected components analysis and centrality analysis.
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This study proposes a performance-based seismic design (PBSD) method for steel braced frames with novel self-centering (SC) braces that utilize shape memory alloys (SMA) as a kernel component.
The SVM classifier is designed by selecting Gaussian RBF kernel as a kernel function.
Each similarity measure that fulfils the kernel properties can be used as a kernel.
Radial basis function was chosen as a kernel.
We used the radial-basis function as a kernel function.
This result, strictly considered, disqualifies K as a kernel density function as kernel density volumes are unitary by definition.
Let us define k x as a kernel similarity function for drugs and k y as a kernel similarity function for target proteins.
We define l to be a centered linear kernel on real-valued phenotypes and k as a kernel on SNP pairs as in equation (4).
We provide a fast calculation of the scale parameters utilizing a Gaussian kernel convolution.
In contrast, Shan et al. [22] only utilize a fixed Gaussian kernel.
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