SO-EBM

This repo contains our code for paper:

End-to-End Stochastic Optimization with Energy-Based Model

Lingkai Kong, Jiaming Cui, Yuchen Zhuang, Rui Feng, B. Aditya Prakash, Chao Zhang

[paper]

Training and Evaluation

Training with the two-stage model:

python two-stage.py --lr 0.001

Training with DFL:

python DFL.py --lr 0.0001

Evaluation for the baselines:

python test_baseline.py 

Training with SO-EBM

python so-ebm.py

Note that DFL and SO-EBM needs to first train the two-stage model as the pre-trained model.

Citation

Please cite the following paper if you find this repo helpful. Thanks!

@inproceedings{kongend,
  title={End-to-end Stochastic Optimization with Energy-based Model},
  author={Kong, Lingkai and Cui, Jiaming and Zhuang, Yuchen and Feng, Rui and Prakash, B Aditya and Zhang, Chao},
  booktitle={Advances in Neural Information Processing Systems}
  year={2022}
}

@article{donti2017task,
  title={Task-based end-to-end model learning in stochastic optimization},
  author={Donti, Priya and Amos, Brandon and Kolter, J Zico},
  journal={Advances in neural information processing systems},
  volume={30},
  year={2017}
}