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External packages needed: * CVXPY is required for all scripts * Install Spearmint https://github.com/JasperSnoek/spearmint * Biopython is required to run the colitis data analysis. Also need to download * the geneset data from Molecular Signatures Database * GDS1615 from the Gene Expression Omnibus database Create folders: * In this directory, create * spearmint_descent directory * results directory * For each example, it will need its own results folder: * e.g. results/matrix_completion_groups/tmp * To run the Colitis data example, create a realdata directory and put the downloaded data into this directory Section 3 results were generated as follows: * Elastic Net: python elasticnet_eval.py * Sparse group lasso: python sgl_eval.py * Sparse Additive models: python sparse_add_models_eval.py Section 4 results were generated as follows: python realdata_eval.py By default, the code solves the joint optimization problem via gradient descent. Specify different solvers (grid search, Spearmint, and nelder-mead) and problem settings via command options.