HN3S: A Federated AutoEncoder Framework for Collaborative Filtering via Hybrid Negative Sampling and Secret Sharing

1. Overview

This repository is an PyTorch Implementation for "HN3S: A Federated AutoEncoder Framework for Collaborative Filtering via Hybrid Negative Sampling and Secret Sharing (IPM 2024)"

Authors: Lu Zhang, Guohui Li, Ling Yuan, Xuanang Ding, Qian Rong
Codes: https://github.com/LukeZane118/HN3S

Note: this project is built upon RecBole, rectorch and FMSS.

2. Environment:

The code was developed and tested on the following python environment:

python 3.8.13
pytorch 1.8.1
colorlog 6.6.0
colorama 0.4.5
pandas 1.2.3
numpy 1.21.5
scipy 1.9.0
munch 2.5.0
Bottleneck 1.3.4
scikit_learn 0.23.2
numba 0.55.2

3. Instructions:

Train and evaluate HN3S:

• To evaluate HN3S on MultDAE
  • bash ./run_multi_dae.sh
• To evaluate HN3S on MultVAE
  • bash ./run_multi_vae.sh
• To evaluate HN3S on RecVAE
  • bash ./run_recvae.sh
• To evaluate HN3S on MacridVAE
  • bash ./run_macridvae.sh