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To reduce nonlinear redundancy, the low-rank-r approximation is suggested to make the kernel projection be feasible for classification.
To solve the two proposed MINL models, a linear regression approximation is suggested to linearize the models; this technique works based on a piecewise linear transformation.
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Further, to efficiently obtain a robust approximation, the support vector regression (SVR) is suggested to construct the surrogate model in the vehicle ORS design process.
Based on some theoretical work, an enhanced version is suggested to improve the approximation.
As a result, many approximation methods have been suggested to compute the integrated (also called marginal) likelihood.
State-of-the-art methods for protein domain detection, like HMMER [ 6], are computationally expensive and several approximation techniques have been suggested to accelerate the model based prediction of protein domains.
The distinctive evolutionary position of Ciona as an invertebrate chordate has been suggested to contain an approximation to the ancestral match of non-duplicated chordate genes; hence it may provide insights into vertebrate evolutionary origins [ 29].
Therefore, it has been suggested to employ i ∈ N fixed-point iterations to compute an approximation to u 1.
The choice of sufficient approximation order is suggested.
In this study, model reference adaptive control algorithm with successive approximation method is suggested for nonlinear systems.
As a result, the system approximation 2 is suggested for the performance evaluation for large networks (with large amount of channels).
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