OnlineLabelShift is the official implementation of the accompanying paper Online Label Shift: Optimal Dynamic Regret meets Practical Algorithms.
For more details, please refer to the paper.
conda env update --file environment.yml
The following command runs the online label shift experiment.
It expects the base model has been trained and saved under /model
python scripts/run_ols.py -d synthetic -m logreg --do-all 1 -t 1000 --save 1
To see all the options
python scripts/run_ols.py -h
This script supports model training for synthetic, cifar10, and mnist datasets.
python scripts/train_model.py -d <data> -m <model> -e <epoch>
The corresponding models are:
| Data | Model |
|---|---|
| synthetic | logreg |
| mnist | fcn |
| cifar10 | resnet18 |
To run experiments on synthetic data, one should first generate the data with the following command:
python scripts/gen_synth_data.py