Use of a selection criterion, such as the Bayesian Information Criterion (BIC), is a form of regularization with a penalty that relies only on the number of coefficients, but not on their magnitude.
One possible explanation for this observation is that the conversion of gene expression data to module activity data may, in fact, function as a form of regularization which removes noise.
An efficient solution to the problem is achieved by using a new form of regularization applied to dual Dini series equations.
The "generalized skyline plot" subsequently introduced by Strimmer and Pybus [ 17] reduces the over-fitting present in the classic skyline plot by applying a simple form of regularization: adjacent intervals that alone are likely to have high stochastic noise are pooled together (cf. Fig. 2b and 2d).
In both visual and textual applications, latent topic models have proven to be a very effective means for this, in essence offering a form of probabilistic regularization or dimensionality reduction that focuses attention on the classes most relevant to the particular example in hand.
Empirical and theoretical results clearly indicate that the DNN training process itself implicitly implements a form of self-regularization, implicitly sculpting a more regularized energy or penalty landscape.
As a common consensus, most methods employ some form of regularization to overcome the problem of many variables but few samples.
This suggests that depending on the structure of the data under consideration, a combined approach where RFs are used to perform dimensionality reduction and some form of regularization on input data before they enter a linear classifier or projection to latent structures might a be viable alternative.
The new form of regularization, termed the Modified Total Generalized Variation (MTGV) regularization, offers a compromise between distinguishing discrete and smooth features in the reconstructed distributions.
We proposed a new iterative regularization method for GIB by iteratively redefining the form of regularization matrix and calculating the corresponding solution.
