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DPER: Efficient Parameter Estimation for Randomly Missing Data

This repo contains scripts to reproduce the results in the paper:

"DPER: Efficient Parameter Estimation for Randomly Missing Data", published in Knowledge-based Systems

Usage

The notebooks are created by Google's Colaboratory and can be run online with Colab

The contents of each notebook is describe as in its title: whether there is the equal covariance matrix assumption + algorithm name(s) + dataset name for big datasets (there is no dataset name the notebook that implements on small datasets).

References

We recommend you to cite our following paper when using these codes for further investigation:

@article{nguyen2021dper,
  title={DPER: Efficient Parameter Estimation for Randomly Missing Data},
  author={Nguyen, Thu and Nguyen-Duy, Khoi Minh and Nguyen, Duy Ho Minh and Nguyen, Binh T and Wade, Bruce Alan},
  journal={arXiv preprint arXiv:2106.05190},
  year={2021}
}

Further requests can directly be sent to the corresponding authors: Thu Nguyen ([email protected]) and Binh T. Nguyen ([email protected]) for an appropriate permission.

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