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mmalekzadeh authored Feb 17, 2020
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Expand Up @@ -11,18 +11,18 @@ Accepted for the Third Conference on Machine Learning and Systems (MLSys 2020),
* Multi-Lable datasets will be automatically downloaded for the firs time.
* For criteo dataset, in the first time, use the script `experiments/Criteo/criteo_dataset/create_datasets.ipynb`

### All you need to begin with:
### (A) All you need to begin with:
#### 1: Run `1_build_an_encoder.ipynb`.
#### 2: Run `2_a_synthetic_exp.ipynb`.

### For Criteo dataset:
### (B) For Criteo dataset:
In the directory `experiments/Criteo/`, we have already run this file for the experiment we have reported in Figure 7 and provided dataset by processing `nrows=1000000000`, that uses 1 billion rows of the original dataset.

I If one desires to make a dataset of another `nrows`, for the first time, the script [`create_datasets.ipynb`](https://github.com/mmalekzadeh/privacy-preserving-bandits/tree/master/experiments/Criteo/criteo_dataset) should be used.
You should first set this parameter (number of rows) in the `create_datasets.ipynb`, build the dataset, and then run the Criteo experiment. Please see [`create_datasets.ipynb`](https://github.com/mmalekzadeh/privacy-preserving-bandits/tree/master/experiments/Criteo/criteo_dataset) for more dtail.


### Info:
### (C) Info:
You may need to install packages that are listed in the `requirements.txt` file.
```
% pip install -r requirements.txt
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