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Figure 13 shows the relation between the regularization parameter (γ w ) of TCWV and the diagonal elements of AKM.
The relation between the regularization parameter of dust model parameters and the diagonal elements of AKM is plotted in Fig. 6.
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Nevertheless, even if the mapping between the regularization parameters exists, this correspondence is not trivial and it is possibly non-linear and discontinuous [17].
And is the regularization parameter which controls the tradeoff between the fidelity term and regularization term.
The regularization parameter, which controls the trade-off between data fidelity and solution size of the regularization problem, exerts a crucial effect on the solution.
The regularization parameter λ quantifies the trade-off between the sparsity and the complexity of the model.
The regularization parameter that defines the trade-off between the mean squared image difference and the smoothness of the deformations was set to four.
The regularization parameter C which control the trade-off between complexity and misclassified training example was set to (10^{5}).
The regularization parameter λ, which controls the trade-off between training misclassification rate and model complexity, is set to a low value of 0.001.
The regularization parameter λ controls the number of nonzero estimated links between nodes and the sparsity of the network.
So that's actually the regularization parameter.
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