This repository contains the beta development of the alocv package, the full version can be found on Wenda Zhou's GitHub.
Computationally effcient approximation of the leave-one-out cross validation risk for (non)-smooth losses and regularizers.
In R console, run devtools::install_github("Francis-Hsu/alocv").
K. Rahnama Rad, A. Maleki (2018). A scalable estimate of the extra-sample prediction error via approximate leave-one-out.
S. Wang, W. Zhou, H. Lu, A. Maleki, and V. Mirrokni (2018). Approximate Leave-One-Out Approximatet for Fast Parameter Tuning in High Dimensions.