Factor Augmented Sparse Throughput Deep ReLU Neural Networks for High Dimensional Regression
用于高维回归的因子增强稀疏直通深度 ReLU 神经网络
This paper introduces a Factor Augmented Sparse Throughput (FAST) model that utilizes both latent factors and sparse idiosyncratic components for nonparametric regression. The FAST model bridges factor models on one end and sparse nonparametric models on the other end. It encompasses structured nonparametric models such as factor augmented additive models and sparse low-dimensional nonparametric interaction models and covers the cases where the covariates do not admit factor…