SRDML

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GitHub Repository for KDD 2022 paper "Saliency-Regularized Deep Multi-Task Learning"

SRDML 최신버젼 다운로드

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# SRDML

This is the code repository for "[Saliency-Regularized Deep Multi-Task Learning](https://dl.acm.org/doi/abs/10.1145/3534678.3539442)" (KDD 2022, Research Track).

We provide the source code for experiments on both synthetic datasets and CIFAR-MTL.

We test our code with Spyder in Anaconda, Python 3.8, TensorFlow-gpu x2.0 on a Windows machine.

1. Synthetic Experiment

- Run synthetic_train.py.

2. CIFAR-MTL

- Run generator_cifar10.py to generate CIFAR-MTL dataset we used in our paper.
   - Run pretrain.py for the pre-training to get the pre-trained model.
   - Run train.py.

For experiments on any other datasets, one can modify the data input pipeline to fit any given dataset.

Our [KDD poster](https://github.com/BaiTheBest/SRDML/blob/main/SRDML%20poster.pdf) is also available.

If you find this code useful in your research, please consider citing:

@inproceedings{bai2022saliency,
        title={Saliency-Regularized Deep Multi-Task Learning},
        author={Bai, Guangji and Zhao, Liang},
        booktitle={Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining},
        pages={15--25},
        year={2022}
    }

SRDML

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