hsm is the R package implementing Algorithm 4 of Yan & Bien (2017)
that uses path-graph-based BCD to solve the proximal operator of latent
group Lasso in hierarchical sparse modeling (HSM). The algorithm solves
the proximal operator using BCD that circles over path graphs decomposed
a directed acyclic graph (DAG).
The package is designed for situation in which latent group Lasso is used to achieve hierarchical sparsity pattern in a DAG. The hierarchical sparsity pattern is one when parameters embedded in a node being set to zero, all the parameters embedded in the descendant nodes in DAG are zeroed out as well.
Yan, X. and Bien, J. (2017). Hierarchical Sparse Modeling: A Choice of Two Group Lasso Formulations. Statist. Sci. 32, no. 4, 531--560. doi:10.1214/17-STS622.