Adversarial-Preference-Learning-with-Pairwise-Comparisons
This is a Keras implementation of the model described in our paper:
Z. Wang, Q. Xu, K. Ma, Y. Jiang, X. Cao and Q. Huang. Adversarial Preference Learning with Pairwise Comparisons. MM2019.
Dependencies
- Keras >= 2.2.4
- Tensorflow >= 1.12.0
- numpy
Data
We convert the datasets ML100K
, ML1M
and Netflix
to our train and test files in the data/
folder.
For each user, we randomly select
The rest ratings are treated as test data and stored in the files *.lsvm. The data format of the line user_id is item_id:rating. The numeric ratings range from 1 to 5.
Train
Here is an example to train the model with logistic loss.
python cr_gan.py
Citation
Please cite our paper if you use this code in your own work:
@inproceedings{wang2019Adversarial,
title={Adversarial Preference Learning with Pairwise Comparisons},
author={Wang, Zitai and Xu, Qianqian and Ma, Ke and Jiang, Yangbangyan and Cao, Xiaochun and Huang, Qingming},
booktitle={ACM on Multimedia Conference},
pages={656--664},
year={2019}
}