May 16, 2024, 4:42 a.m. | Jose A. Lopez, Georg Stemmer, Hector A. Cordourier

cs.LG updates on arXiv.org arxiv.org

arXiv:2405.09305v1 Announce Type: new
Abstract: Gradient boosted decision trees have achieved remarkable success in several domains, particularly those that work with static tabular data. However, the application of gradient boosted models to signal processing is underexplored. In this work, we introduce gradient boosted filters for dynamic data, by employing Hammerstein systems in place of decision trees. We discuss the relationship of our approach to the Volterra series, providing the theoretical underpinning for its application. We demonstrate the effective generalizability of …

abstract application arxiv cs.lg data decision decision trees domains dynamic filters gradient however processing signal success systems tabular tabular data trees type work

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