Required packages

• PyTorch
• kmeans_pytorch
• sklearn

Commands

Experiment on Credit Card Data Set with non-contrastive reguarlization.

python main.py -d credit -mode ncontra

Experiment on Credit Card Data Set with contrastive reguarlization.

python main.py -d credit -mode contra -alpha 5

Flags:

• -d: data set
• -g: the index of the gpu
• -hid: the hidden feature dimension
• -alpha: the coefficient of fairness constraint
• -beta: the coefficient of contrastive or non-contrastive regularization
• -gamma: the coefficient of KL divergence loss
• -miss: whether to enable missing feature scenario
• -purturbed: whether to enable noisy feature scenario
• -mode: use contrastive or non-contrastive regularizatio (default: non-contrastive regularization)

Reference

@inproceedings{zheng2023fairness, title={Fairness-aware Multi-view Clustering}, author={Zheng, Lecheng and Zhu, Yada and He, Jingrui}, booktitle={Proceedings of the 2023 SIAM International Conference on Data Mining (SDM)}, pages={856--864}, year={2023}, organization={SIAM} }