xiaoxinlong/kdd23_efin

Experiments codes for SIGKDD '23 paper "Explicit Feature Interaction-aware Uplift Network for Online Marketing"

KDD23_EFIN

Experiments codes for the paper:

Dugang Liu, Xing Tang, Han Gao, Fuyuan Lyu, Xiuqiang He. Explicit Feature Interaction-aware Uplift Network for Online Marketing. In Proceedings of SIGKDD '23.

Please cite our SIGKDD '23 paper if you use our codes. Thanks!

Requirement

• python==3.8.5
• torch==1.13.1+cu117
• optuna==2.10.0

Usage

Since the dataset file is too large, please obtain it from the original web page and place it in folder "datax/X". For Criteo dataset, the command line examples are as follows:

For data processing:

python get_criteo.py

For hyperparameter search and training:

CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 nohup python -m torch.distributed.launch --nproc_per_node=8 tune_efin.py > tune_efin 2>&1 &

More results

The benchmark we developed is under review at the conference and contains more baselines, preprocessing, and datasets. We will open source and maintain it continuously after it is accepted. Please stay tuned!

If you have any issues or ideas, feel free to contact us ([email protected]).