Sure Independence Screening
Regularized Generalized Linear Models with Interaction Effects
R Programming: Zero to Pro
Neyman-Pearson (NP) Classification Algorithms and NP Receiver
Build Dependency Graphs using Projection
Random Subspace Ensemble Classification and Variable Screening
Transfer Learning under Regularized Generalized Linear Models
Neyman-Pearson Classification via Cost-Sensitive Learning
Unsupervised Multi-Task and Transfer Learning on Gaussian