The system of images for a regularized element consists of a set of several elements, usually of higher order, that produce a flow that is zero at the bounding plane.
During the back-propagation process, the network must iteratively minimize a regularized error function which we will set to the expression (12) in the following sections.
In the second step, we estimate a regularized linear regression (Haykin 2008) from a training set that consists of tuples, (D^f=left{ {( {f_1,y_1 }),( {f_2,y_2 }),ldots,( {f_n,y_n })} right} ).
This explains why a regularized estimator brings about benefits also if the set S is chosen to be relatively small (e.g., 10 variables).
A regularized Hotelling T2 procedure was used to identify sets of proteins, defined by biological pathways, that differ in concentrations between cases and controls for each study disease.
As with the GPR model, we also apply a MIMO approach by estimating a regularized linear regression (Haykin 2008), and generate the vectorial forecasts using the set of regularized coefficients.
A regularized version of the model is constructed based on the level-set method.
The proposed developments are integrated into a computational platform based on a regularized boundary integral equation (BIE) method for 3D elastodynamics, and illustrated via a set of canonical numerical experiments.
The aberrant trials in the training set would contribute minimally to the learning of optimal weights because we used a regularized classifier to reduce the effects of outliers [7].
Initialization with a constant function (adaptive regularized level set (ARLS) model [28]) (Figure 3f,g): Φinitial = ∓ c 0 in Ω. Edge-based level set methods have some drawbacks.
Yeo et al. developed a regularized least-squares classifier, called ACESCAN [ 16], to identify cassette exons in human/mouse orthologs using a similar feature set.
