/RECORD

Demo for the paper "RECORD: Resource Constrained Semi-Supervised Learning under Distribution Shift"

Primary LanguagePython

RECORD

This is a demo for the paper: "RECORD: Resource Constrained Semi-Supervised Learning under Distribution Shift".

Prerequisites
  • Python 3.7
  • Pytorch
  • scikit-learn
  • h5py
  • matplotlib
Folders
  • src: Python source code.
  • data: Placeholder for the dataset. Please download the dataset from Google Drive.
  • logs: Placeholder for the running logs.
  • images: Placeholder for the line charts.
To Run

For example, you can run the following command in the root path:

python ./src/run.py

The result will be saved in logs folder with a line chart saved in the images folder.

In this demo, we prepared four benchmark data sets for the distribution shift and three implements of semi-supervised learning methods. You can also use command python ./src/run.py -h to list the usages.

Contact wnjxyk@gmail.com for more questions.