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2020-09-17 11:22:50 +00:00
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README.md
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@@ -141,4 +141,4 @@ If you want to contribute to this repo, please see [CONTRIBUTING.md](.github/CON
Besides, please follow [CODE-OF-CONDUCT.md](.github/CODE-OF-CONDUCT.md). Besides, please follow [CODE-OF-CONDUCT.md](.github/CODE-OF-CONDUCT.md).
# License # License
The entire codebase is under [MIT license](LICENSE.md) The entire codebase is under the [MIT license](LICENSE.md).

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README_CN.md
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@@ -98,13 +98,13 @@ Some methods use knowledge distillation (KD), which require pre-trained models.
如果您发现该项目对您的科研或工程有帮助，请考虑引用下列的某些文献： 如果您发现该项目对您的科研或工程有帮助，请考虑引用下列的某些文献：
``` ```
@inproceedings{dong2020nasbench201,
@article{dong2020nats, @article{dong2020nats,
title={NATS-Bench: Benchmarking NAS algorithms for Architecture Topology and Size}, title={NATS-Bench: Benchmarking NAS algorithms for Architecture Topology and Size},
author={Dong, Xuanyi and Liu, Lu and Musial, Katarzyna and Gabrys, Bogdan}, author={Dong, Xuanyi and Liu, Lu and Musial, Katarzyna and Gabrys, Bogdan},
journal={arXiv preprint arXiv:2009.00437}, journal={arXiv preprint arXiv:2009.00437},
year={2020} year={2020}
} }
@inproceedings{dong2020nasbench201,
title = {NAS-Bench-201: Extending the Scope of Reproducible Neural Architecture Search}, title = {NAS-Bench-201: Extending the Scope of Reproducible Neural Architecture Search},
author = {Dong, Xuanyi and Yang, Yi}, author = {Dong, Xuanyi and Yang, Yi},
booktitle = {International Conference on Learning Representations (ICLR)}, booktitle = {International Conference on Learning Representations (ICLR)},