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Multiparameter regularization and aggregation in the context of polynomial functional regression
May 8, 2024, 4:42 a.m. | Elke R. Gizewski, Markus Holzleitner, Lukas Mayer-Suess, Sergiy Pereverzyev Jr., Sergei V. Pereverzyev
cs.LG updates on arXiv.org arxiv.org
Abstract: Most of the recent results in polynomial functional regression have been focused on an in-depth exploration of single-parameter regularization schemes. In contrast, in this study we go beyond that framework by introducing an algorithm for multiple parameter regularization and presenting a theoretically grounded method for dealing with the associated parameters. This method facilitates the aggregation of models with varying regularization parameters. The efficacy of the proposed approach is assessed through evaluations on both synthetic and …
abstract aggregation algorithm arxiv beyond context contrast cs.lg cs.na exploration framework functional math.na math.st multiple polynomial presenting regression regularization results stat.ml stat.th study type
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