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In order to avoid overfitting and instead of adding a regularization parameter in the criterion, early stopping is introduced as a regularization method for HK learning, which becomes HKES (Ho Kashyap with early stopping).
As a regularization method, the Tikhonov method has been used to solve ill-posed problems in a number of publications.
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In Chapter 1, we propose a regularization method for sparse estimation for estimating equations.
As large values of anisotropy lead to an ill-posed phase-field equation we present a regularization method capable of circumvent non-differentiable domains of interfacial energy.
A regularization method is thus required.
Therefore, a regularization method is extremely important.
Hence, a regularization method is needed.
In Section 3, a regularization method is investigated.
In this article, we propose a regularization method by modifying the 'kernel' to deal with the difficulty of problem (1) as follows: frac{e^{l xi 1-xx)}}{1+beta^{2}e^{2|xi|^{alpha}cos{frac{e^{l xi 1-x}}{, where β is a regularization parameter.
In a regularization method by the duality operator, we use the degree theories of Kartsatos and Skrypnik upon conditions of C as well as Browder's degree.
The viscosity method for nonexpansive mappings is essentially a regularization method of nonexpansive mappings by contractions.
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