Merge branch 'master' of https://github.com/mmalekzadeh/privacy-prese…

…rving-bandits

README.md

@@ -11,14 +11,24 @@ 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`.
 
+### (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:
-If you don't run `1_build_an_encoder.ipynb`, you may need to install these libraries:
+
+### (C) Info:
+You may need to install packages that are listed in the `requirements.txt` file.
+ ```
+ % pip install -r requirements.txt 
+ ```
+
+Specifically, these libraries:
 ```
 %pip install iteround
 %pip install pairing