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TV is a specific regularization method with advantage of non-restricting solution to be smooth [25].
We show that a nonparametric estimator of a regression function, obtained as solution of a specific regularization problem is the best linear unbiased predictor in some nonparametric mixed effect model.
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As an illustration, we consider the following specific regularization.
Regularization introduces a prior that imposes constraints in the STRF estimate and, under noisy conditions, the specific regularization used by the model can introduce biases in the estimates [4].
This position specific regularization leaves the conserved positions of the matrix relatively unchanged.
To conclude this section, note that shrinkages and regularization procedures are linked in the sense that a shrinkage function solves to a regularization problem constrained by a specific penalty function [16].
A specific formulation of the proposed method, called hybrid regularization, is introduced and investigated.
The selection of a range of regularization parameter values for solving a specific inverse problem is specific to that inverse problem.
In this paper we present a manifold regularization technique to constrain the low dimensional manifold to a specific range of possible manifold shapes, the range being determined via a statistical shape model of manifolds (SSMM).
The results indicate that a specific architecture of feed-forward neural networks, which are trained by Bayesian regularization back-propagation algorithm, has the best performance for the reactor states reconstruction.
A specific point emphasized is that the strength criterion must be augmented by an appropriate regularization strategy if the post-localization response is to be evaluated.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com