Stochastic Multiple Target Sampling Gradient Descent

This repository contains the Pytorch implementation of Stochastic Multiple Target Sampling Gradient Descent.

If you find our code useful in your research, please cite:

@article{phan2022stochastic,
  title={Stochastic Multiple Target Sampling Gradient Descent},
  author={Phan, Hoang and Tran, Ngoc and Le, Trung and Tran, Toan and Ho, Nhat and Phung, Dinh},
  journal={Advances in Neural Information Processing Systems},
  year={2022}
}

Our implementation consists of 4 subexperiments:

• CelebA
• Multi-MNIST/Fashion/Fashion and MNIST
• Multivariate Regression
• Toy example

Data:

• CelebA
• Multi-MNIST/Fashion/Fashion and MNIST
• Multivariate Regression

Reproducing:

Please refer to the bash script (*.sh) in each experiment to reproduce the reported results in the paper.

For the running time of our approach, you can take a look at this notebook in Google Colab as we wanted to utilize the cloud computing service for a fair comparison.

Contact

If you have any questions about the paper or the codebase, please feel free to contact [email protected].