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mixval's Introduction

Code for MixVal@NeurIPS 2023

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 mixval_run0.sh.

Citation

@inproceedings{hu2023mixed,
    title={Mixed Samples as Probes for Unsupervised Model Selection in Domain Adaptation},
    author={Dapeng Hu and Jian Liang and Jun Hao Liew and Chuhui Xue and Song Bai and Xinchao Wang},
    booktitle={Thirty-seventh Conference on Neural Information Processing Systems},
    year={2023}
}

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