Systems and methods for updating a machine-learning-based prediction model with preserved privacy

Abstract

The disclosed computer-implemented method for updating a machine-learning-based prediction model with preserved privacy may include receiving a plurality of training data sets for training a machine-learning-based global prediction model for predicting future incidents of a computing event. Each data set may include incidents of the computing event. The method may include creating, by training the global prediction model using the plurality of training data sets, an intermediate prediction model of the global prediction model. The intermediate prediction model may be a precursor state to a fully trained global prediction model. The method may further include providing the intermediate prediction model to a computing node to enable the computing node to fully train a local prediction model using both the intermediate prediction model and a local training data set. Various other methods, systems, and computer-readable media are also disclosed.