5 citations · 9 across the 3 of their papers we have counts for
3 papers
stat.ML2023
Sparse-Input Neural Network using Group Concave Regularization
Bin Luo, Susan Halabi
Simultaneous feature selection and non-linear function estimation is challenging in modeling, especially in high-dimensional settings where the number of variables exceeds the avai…
stat.ME2019★ 4 cited
A High-dimensional M-estimator Framework for Bi-level Variable Selection
Bin Luo, Xiaoli Gao
In high-dimensional data analysis, bi-level sparsity is often assumed when covariates function group-wisely and sparsity can appear either at the group level or within certain grou…
math.ST2019★ 5 cited
High-dimensional robust approximated M-estimators for mean regression with asymmetric data
Bin Luo, Xiaoli Gao
Asymmetry along with heteroscedasticity or contamination often occurs with the growth of data dimensionality. In ultra-high dimensional data analysis, such irregular settings are u…