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George Tzougas and Konstantin Kutzkov
We developed a methodology for the neural network boosting of logistic regression aimed at learning an additional model structure from the data. In particular, we constructed two classes of neural network-based models: shallow?dense neural networks with ...
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Olga Kostyukova and Tatiana Tchemisova
In this paper, we continue an earlier study of the regularization procedures of linear copositive problems and present new algorithms that can be considered as modifications of the algorithm described in our previous publication, which is based on the co...
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Innocent Mudhombo and Edmore Ranganai
Although the variable selection and regularization procedures have been extensively considered in the literature for the quantile regression (????)
(
Q
R
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scenario via penalization, many such procedures fail to deal with data aberrations in the design ...
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