sglOptim: Sparse group lasso generic optimizer
Fast generic solver for sparse group lasso optimization problems.
The loss (objective) function must be defined in a C++ module. This package
apply template metaprogramming techniques, therefore – when compiling the
package from source – a high level of optimization is needed to gain full
speed (e.g. for the GCC compiler use -O3). Use of multiple processors for
cross validation and subsampling is supported through OpenMP. The Armadillo
C++ library is used as the primary linear algebra engine.