2 papers
stat.ME2026
LARGE: A Locally Adaptive Regularization Approach for Estimating Gaussian Graphical Models
Ha Nguyen, Sumanta Basu
The graphical Lasso (GLASSO) is a widely used algorithm for learning high-dimensional undirected Gaussian graphical models (GGM). Given i.i.d. observations from a multivariate norm…
stat.ME2025
Autotune: fast, accurate, and automatic tuning parameter selection for Lasso
Tathagata Sadhukhan, Ines Wilms, Stephan Smeekes +1
Least absolute shrinkage and selection operator (Lasso), a popular method for high-dimensional regression, is now used widely for estimating high-dimensional time series models suc…