Use of EM algorithm for data reduction under sparsity assumption

@article{Ghosh2017UseOE,
  title={Use of EM algorithm for data reduction under sparsity assumption},
  author={Atanu Kumar Ghosh and Arnab Chakraborty},
  journal={Computational Statistics},
  year={2017},
  volume={32},
  pages={387-407}
}
Recent scientific applications produce data that are too large for storing or rendering for further statistical analysis. This motivates the construction of an optimum mechanism to choose only a subset of the available information and drawing inferences about the parent population using only the stored subset. This paper addresses the issue of estimation of parameter from such filtered data. Instead of all the observations we observe only a few chosen linear combinations of them and treat the… CONTINUE READING

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EM*: An EM Algorithm for Big Data

  • 2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA)
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