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# Reference
**paper**
- 09/2018 [Searching for Efficient Multi-Scale Architectures for Dense Image Prediction](https://arxiv.org/abs/1809.04184)
- 10/2018 [Fast Neural Architecture Search of Compac…
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# Reference
- [ ] [paper - 2017 - Google Vizier: A Service for Black-Box Optimization](https://static.googleusercontent.com/media/research.google.com/zh-CN//pubs/archive/46180.pdf)
- [ ] [automl…
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# Reference
# Brief
## Pruning
Name | Description
-- | --
AGP Pruner
Slim Pruner
FPGM Pruner
NetAdapt Pruner
SimulatedAnnealing Pruner
ADMM Pruner
AutoCompress Pruner
Prune-EA
#…
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# Reference
- [ ] [Github repo](https://github.com/EpistasisLab/tpot)
- [ ] [Docs](http://epistasislab.github.io/tpot/)
# Brief
- A Python Automated Machine Learning tool that optimizes machine …
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# Reference
- [ ] [github repo](https://github.com/tensorflow/adanet)
- [ ] [Document](https://adanet.readthedocs.io/en/v0.5.0/)
- [ ] [利用 AdaNet 将多个 TensorFlow Hub 模块组合成一个集成网络](https://mp.weixin…
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Can we have an example on how to host the custom model on the cloud and access it through the app? The example only shows how to run a locally stored model. Thanks
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I couldn't get the same result with FLAML when using the original ML model trained with the configuration obtained from FLAML.
Below is my code for FLAML and the result:
```
automl = AutoML()
au…
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**System Information (please complete the following information):**
- Model Builder Version (available in Manage Extensions dialog): 16.13.9.2235601
- Visual Studio Version: 17.5.2
Microsoft.ML 3…
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## Neural Architecture Search with Reinforcement Learning
- 第一篇比较正式的 RL-Based NAS paper
- RL
- Agent - RNN - Controller - `A variable-length String`
- Reward - Accuracy
- Policy Gradient
…
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# NASNet
- Learning Transferable Architectures for Scalable Image Recognition
- 基于 [Neural Architecture Search with Reinforcement Learning](https://arxiv.org/abs/1611.01578)
- `Normal Cell` - 输…