Skip to content

DamianStraszak/FairDiverseDPPSampling

Repository files navigation

FairDiverseDPPSampling

This repository provides an implementation in python of a fair and diverse sampling mechanism based on DPPs (Determinantal Point Processes) along with experiments comparing several exising sampling methods as presented in our ICML'18 paper (available here https://arxiv.org/abs/1802.04023).

Using the code

  1. If you want to see a simple demonstration of DPP sampling see "example_sampling.py".
  2. If you want to run the experiments using the image data-set run "run_image_experiment.py".
  3. If you want to run the experiments using the adult data-set run "run_adult_experiment.py".

References

Fair and Diverse DPP-Based Data Summarization
L. Elisa Celis, Vijay Keswani, Damian Straszak, Amit Deshpande, Tarun Kathuria, Nisheeth K. Vishnoi
International Conference on Machine Learning, ICML 2018

Please cite the corresponding paper when using the code.

About

No description or website provided.

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published