PROMISE

Companion code for "PROMISE: Preconditioned Stochastic Optimization Methods by Incorporating Scalable Curvature Estimates". We provide detailed instructions for reproducing each plot in the paper.

📝 Note
We plan to create a version of PROMISE that is easy for practitioners to use in the near future!

Preliminary steps

1. Download the required datasets to a new folder data by running python download_data.py. You may have to use the command data_fixes.sh ./data to fix some issues in the higgs, susy, and webspam datasets. To use the yelp dataset in the showcase experiments , please visit https://www.yelp.com/dataset and preprocess the dataset using yelp_preprocessing.py.

2. Remove the folders performance_results, suboptimality_results, showcase_results, streaming_results, sensitivity_results, spectra_results, and regularity_results.

After completing the preliminary steps, we can run shell scripts (.sh) in the config folder and notebooks (.ipynb) in the plotting folder to generate the plots.

Performance experiments (Section 6.1)

First, please run sklearn_opt_least_squares.sh, sklearn_opt_logistic.sh, sklearn_opt_least_squares_mu_1e-1.sh, and sklearn_opt_logistic_mu_1e-1.sh.

Then run performance_exp_least_squares.sh, performance_exp_logistic.sh, performance_exp_least_squares_mu_1e-1.sh, and performance_exp_logistic_mu_1e-1.sh.

Once these scripts are finished running, please run performance_results_plots.ipynb.

Suboptimality experiments (Section 6.2)

Please run suboptimality_exp_least_squares.sh and suboptimality_exp_logistic.sh.

Once these scripts are finished running, please run suboptimality_results_plots.ipynb.

Showcase experiments (Section 6.3)

Please run showcase_exp_url.sh, showcase_exp_yelp.sh, and showcase_exp_acsincome.sh.

Once these scripts are finished running, please run showcase_results_plots.ipynb. This notebook will also generate Figure 1 in the Introduction (Section 1).

Streaming experiments (Section 6.4)

Please run streaming_exp_logistic_higgs.sh and streaming_exp_logistic_susy.sh.

Once these scripts are finished running, please run streaming_results_plots.ipynb.

Sensitivity study (Section 6.5)

Please run sensitivity_exp_least_squares.sh, sensitivity_exp_logistic.sh, and compute_spectra.sh.

Once these scripts are finished running, please run sensitivity_results_plots.ipynb and spectrum_results_plots.ipynb.

Regularity study (Section 6.6)

Please run regularity_exp_logistic.sh.

Once this script is finished running, please run regularity_results_plots.ipynb.

⚠️ Warning
Running all the experiments can take a lot of time. If you would like to generate plots based on existing results in performance_results, suboptimality_results, showcase_results, streaming_results, sensitivity_results, spectra_results, and regularity results, just run the corresponding notebooks mentioned above.