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6
README.md
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@ -392,7 +392,8 @@ If you've found BigDL useful for your project, you may cite our papers as follow
booktitle={2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
year={2022},
pages={21407-21414},
doi={10.1109/CVPR52688.2022.02076}}
doi={10.1109/CVPR52688.2022.02076}
}
```
- *[BigDL](https://arxiv.org/abs/1804.05839): A Distributed Deep Learning Framework for Big Data*
@ -403,6 +404,7 @@ If you've found BigDL useful for your project, you may cite our papers as follow
booktitle = {Proceedings of the ACM Symposium on Cloud Computing (SoCC)},
year = {2019},
pages = {50–60},
doi = {10.1145/3357223.3362707},
doi = {10.1145/3357223.3362707}
}
```

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docs/readthedocs/source/index.rst
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@ -1,7 +1,7 @@
BigDL Documentation
BigDL: fast, distributed, secure AI for Big Data
===========================
BigDL seamlessly scales your data analytics & AI applications from laptop to cloud, with the following libraries:
`BigDL <https://github.com/intel-analytics/bigdl>`_ seamlessly scales your data analytics & AI applications from laptop to cloud, with the following libraries:
- `Orca <doc/Orca/index.html>`_: Distributed Big Data & AI (TF & PyTorch) Pipeline on Spark and Ray
- `Nano <doc/Nano/index.html>`_: Transparent Acceleration of Tensorflow & PyTorch Programs