4 papers
S2MAM: Semi-supervised Meta Additive Model for Robust Estimation and Variable Selection
Xuelin Zhang, Hong Chen, Yingjie Wang +2
Semi-supervised learning with manifold regularization is a classical framework for jointly learning from both labeled and unlabeled data, where the key requirement is that the supp…
Meta Additive Model: Interpretable Sparse Learning With Auto Weighting
Xuelin Zhang, Xinyue Liu, Lingjuan Wu +1
Sparse additive models have attracted much attention in high-dimensional data analysis due to their flexible representation and strong interpretability. However, most existing mode…
Beyond False Discovery Rate: A Stepdown Group SLOPE Approach for Grouped Variable Selection
Xuelin Zhang, Jingxuan Liang, Xinyue Liu +2
High-dimensional feature selection is routinely required to balance statistical power with strict control of multiple-error metrics such as the k-Family-Wise Error Rate (k-FWER) an…
Generalized Sparse Additive Model with Unknown Link Function
Peipei Yuan, Xinge You, Hong Chen +2
Generalized additive models (GAM) have been successfully applied to high dimensional data analysis. However, most existing methods cannot simultaneously estimate the link function,…