Skip to content

takeuchi-lab/DRCS

Repository files navigation

Code for the experiment in the paper "Distributionally Robust Coreset Selection under Covariate Shift"

Authors: Tomonari Tanaka, Hiroyuki Hanada, Hanting Yang, Aoyama Tatsuya, Yu Inatsu, Akahane Satoshi, Yoshito Okura, Noriaki Hashimoto, Taro Murayama, Hanju Lee, Shinya Kojima, Ichiro Takeuchi

Transactions on Machine Learning Research, to appear

URL: https://openreview.net/forum?id=Eu7XMLJqsC

Setup

Programs are implemented in Python.

The following packages can be installed via pip or conda:

  • numpy
  • scipy
  • scikit-learn
  • matplotlib
  • cvxpy
  • pytorch (required only when we specify cifar10 as a dataset)
  • torchvision (required only when we specify cifar10 as a dataset)

The following package can be installed by compiling with C++ compiler (gcc, g++ and make are required) and then via pip:

Experiments

Run the followings:

  • ./experiment_drcs.sh: Model performance of DRCS

Copyright notice

All programs are written by the authors.

Dataset files are retrieved from "LIBSVM Data" by Rong-En Fan (National Taiwan University). https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/

About

Distributionally Robust Coreset Selection under Covariate Shift (Transactions on Machine Learning Research)

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors