A Critical Overview of Privacy-Preserving Approaches for Collaborative Forecasting

20 Apr 2020Carla GonçalvesRicardo J. BessaPierre Pinson

Cooperation between different data owners may lead to an improvement in forecast quality - for instance by benefiting from spatial-temporal dependencies in geographically distributed time series. Due to business competitive factors and personal data protection questions, said data owners might be unwilling to share their data, which increases the interest in collaborative privacy-preserving forecasting... (read more)

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