Search Results for author:
Found 1 papers, 0 papers with code
ET-Lasso: A New Efficient Tuning of Lasso-type Regularization for High-Dimensional Data
The pseudo-features are constructed to be inactive by nature, which can be used to obtain a cutoff to select the tuning parameter that separates active and inactive features.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
