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On regularized polynomial functional regression
May 8, 2024, 4:43 a.m. | Markus Holzleitner, Sergei Pereverzyev
cs.LG updates on arXiv.org arxiv.org
Abstract: This article offers a comprehensive treatment of polynomial functional regression, culminating in the establishment of a novel finite sample bound. This bound encompasses various aspects, including general smoothness conditions, capacity conditions, and regularization techniques. In doing so, it extends and generalizes several findings from the context of linear functional regression as well. We also provide numerical evidence that using higher order polynomial terms can lead to an improved performance.
abstract article arxiv capacity context cs.lg cs.na functional general linear math.na math.st novel polynomial regression regularization sample stat.th treatment type
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