2018
A Unified Dynamic Approach to Sparse Model Selection
AISTATS 2018poster
Sparse model selection is ubiquitous from linear regression to graphical models where regularization paths, as a family of estimators upon the regularization parameter varying, are computed when the regularization parameter is unknown or decided data-adaptively. Traditional computational methods rel…