Invariant Debiasing Learning for Recommendation via Biased Imputation

This repository contains the code for the paper "Invariant Debiasing Learning for Recommendation via Biased Imputation," which has been accepted by Information Processing and Management(IPM).

Environment Requirements

• Python Version: 3.8.0

Installation Steps

STEP 1: Prepare Datasets

1. Download Datasets:

   • Yahoo!R3: https://webscope.sandbox.yahoo.com/catalog.php?datatype=r&did=3

   • COAT: https://www.cs.cornell.edu/schnabts/mnar/

2. Configure Datasets Paths:

   • Configure local datasets paths in global_config.py.

STEP 2: Run the Models

1. Configure local paths for results saving in global_config.py
2. Run main_xxx.py to train models

Citation

If you use this project in your research, please cite the following paper:

@article{bai2025invariant,
  title={Invariant debiasing learning for recommendation via biased imputation},
  author={Bai, Ting and Chen, Weijie and Yang, Cheng and Shi, Chuan},
  journal={Information Processing \& Management},
  volume={62},
  number={3},
  pages={104028},
  year={2025},
  publisher={Elsevier}
}