Code for EnsV

Simplifying and Stabilizing Model Selection in Unsupervised Domain Adaptation

Prerequisites

• python == 3.7.13
• cudatoolkit == 10.1.243
• pytorch ==1.7.1
• torchvision == 0.8.2
• numpy, scikit-learn, PIL, argparse

Demo

• Configure the PyTorch environment.
• Download the Office-Home dataset. Configure the data lists in data and the checkpoints in ckpts.
• Run the code in ensv.sh.

Citation

@inproceedings{hu2023simplifying,
    title={Simplifying and Stabilizing Model Selection in Unsupervised Domain Adaptation},
    author={Dapeng Hu and Mi Luo and Jian Liang and Chuan-Sheng Foo},
    booktitle={NeurIPS 2023 Workshop on Distribution Shifts: New Frontiers with Foundation Models},
    year={2023}
}

Contact

• lhxxhb15@gmail.com