AINeutralarXiv – CS AI · 6h ago6/10
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Neural Additive and Basis Models with Feature Selection and Interactions
Researchers propose enhanced neural additive and basis models (NAM/NBM) that incorporate feature selection mechanisms to improve computational efficiency and interpretability of deep neural networks. The advancement enables these models to handle high-dimensional datasets and capture feature interactions while reducing training costs and model sizes compared to traditional approaches.