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This project is the code and the supplementary of "Personalized Federated Collaborative Filtering: A Variational AutoEncoder Approach"

1. The code is implemented with Python ~= 3.8 and torch~=2.3.1+cu117;
2. Other requirements can be installed by pip install -r requirements.txt.

Notice: FedDAE was previously referred to as FedMAE, so terms like "MAE" may appear in the code.

1. Put datasets into the path [parent_folder]/datasets/;

2. For quick start, please run:

   python main.py --alias FedMAE --dataset movielens --data_file ml-100k.dat \
       --lr 1e-3 --l2_reg 1e-5 --seed 0
   

3. if you want to use the notice function mail_notice, please set your own keys.

In the implementation of this project, we referred to the code of RecBole and Tenrec, and we are grateful for their open-source contributions!

• This project is free for academic usage. You can run it at your own risk.
• For any other purposes, please contact Mr. Zhiwei Li ([email protected])