4 papers
Numerical optimization for the compatibility constant of the lasso
Kei Hirose
The compatibility constant plays an important role in evaluating the prediction error of the lasso in high-dimensional settings. However, the computation of the compatibility const…
Data-driven configuration tuning of glmnet for balancing accuracy and computational efficiency
Shuhei Muroya, Kei Hirose
The glmnet package in R is widely used for lasso estimation because of its computational efficiency. Despite its popularity, glmnet occasionally yields solutions that deviate subst…
Robust and consistent model evaluation criteria in high-dimensional regression
Sumito Kurata, Kei Hirose
Most of the regularization methods such as the LASSO have one (or more) regularization parameter(s), and to select the value of the regularization parameter is essentially equal to…
Clustering-based aggregate value regression
Kei Hirose, Hidetoshi Matsui, Hiroki Masuda
In various practical situations, forecasting of aggregate values rather than individual ones is often our main focus. For instance, electricity companies are interested in forecast…