CompositeProblems

Layout (additive) composite problems and associated oracles. The nonsmooth part is based on StructuredProximalOperators.

Implemented problems

• least squares + l1 regularization
  • get_lasso_MLE
• logistic + l1 regularization
  • get_logit_MLE
• trace norm + l regularization
  • get_tracenorm_MLE

Example: least-squares with l1 penalization.

julia> using CompositeProblems
julia> n, m, sparsity = 10, 8, 0.8
julia> pb = get_logit_MLE(n=n, m=m, sparsity=0.8);
julia> x = rand(n);
julia> h = rand(n);
julia> res = zeros(n);

julia> f(pb, x)

julia> ∇f!(pb, res, x);
julia> ∇f(pb, x);

julia> ∇²f_h!(pb, res, x, h);
julia> ∇²f_h(pb, x, h);

julia> get_gradlips(pb);

About instances

Some problems use the data from libsvm:

• ionosphere: automatic download;
• gisette: download by hand of file gisette_scale.bz2, which should be decompressed in folder instances.