4 papers
FoReco and FoRecoML: A Unified Toolbox for Forecast Reconciliation in R
Daniele Girolimetto, Jeroen Rombouts, Ines Wilms +1
Forecast reconciliation has become key to improving the accuracy and coherence of forecasts for linearly constrained multiple time series, such as hierarchical and grouped series.…
MLOps Monitoring at Scale for Digital Platforms
Yu Jeffrey Hu, Jeroen Rombouts, Ines Wilms
Machine learning models are widely recognized for their strong performance in forecasting. To keep that performance in streaming data settings, they have to be monitored and freque…
Cross-Temporal Forecast Reconciliation at Digital Platforms with Machine Learning
Jeroen Rombouts, Marie Ternes, Ines Wilms
Platform businesses operate on a digital core and their decision making requires high-dimensional accurate forecast streams at different levels of cross-sectional (e.g., geographic…
Monitoring Machine Learning Forecasts for Platform Data Streams
Jeroen Rombouts, Ines Wilms
Data stream forecasts are essential inputs for decision making at digital platforms. Machine learning algorithms are appealing candidates to produce such forecasts. Yet, digital pl…