An Aggregate Learning Approach for Interpretable Semi-Supervised Population Prediction and Disaggregation Using Ancillary Data

@article{Derval2019AnAL,
  title={An Aggregate Learning Approach for Interpretable Semi-Supervised Population Prediction and Disaggregation Using Ancillary Data},
  author={Guillaume Derval and Fr{\'e}d{\'e}ric Docquier and Pierre Schaus},
  journal={ArXiv},
  year={2019},
  volume={abs/1907.00270}
}
Census data provide detailed information about population characteristics at a coarse resolution. Nevertheless, fine-grained, high-resolution mappings of population counts are increasingly needed to characterize population dynamics and to assess the consequences of climate shocks, natural disasters, investments in infrastructure, development policies, etc. Dissagregating these census is a complex machine learning, and multiple solutions have been proposed in past research. We propose in this… 
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