no code implementations • 21 Dec 2022 • Christoph Bergmeir, Frits de Nijs, Abishek Sriramulu, Mahdi Abolghasemi, Richard Bean, John Betts, Quang Bui, Nam Trong Dinh, Nils Einecke, Rasul Esmaeilbeigi, Scott Ferraro, Priya Galketiya, Evgenii Genov, Robert Glasgow, Rakshitha Godahewa, Yanfei Kang, Steffen Limmer, Luis Magdalena, Pablo Montero-Manso, Daniel Peralta, Yogesh Pipada Sunil Kumar, Alejandro Rosales-Pérez, Julian Ruddick, Akylas Stratigakos, Peter Stuckey, Guido Tack, Isaac Triguero, Rui Yuan
As both forecasting and optimization are difficult problems in their own right, relatively few research has been done in this area.
no code implementations • 15 Sep 2022 • Alexey Chernikov, Chang Wei Tan, Pablo Montero-Manso, Christoph Bergmeir
Traditionally, features used in TSF are handcrafted, which requires domain knowledge and significant data-engineering work.
no code implementations • 8 Aug 2021 • Hansika Hewamalage, Pablo Montero-Manso, Christoph Bergmeir, Rob J Hyndman
Scale normalization of the M5 error measure results in less stability than other scale-free errors.
1 code implementation • 14 May 2021 • Rakshitha Godahewa, Christoph Bergmeir, Geoffrey I. Webb, Rob J. Hyndman, Pablo Montero-Manso
Many businesses and industries nowadays rely on large quantities of time series data making time series forecasting an important research area.
1 code implementation • 16 Oct 2020 • Rakshitha Godahewa, Christoph Bergmeir, Geoffrey I. Webb, Pablo Montero-Manso
Many businesses and industries require accurate forecasts for weekly time series nowadays.
1 code implementation • 2 Aug 2020 • Pablo Montero-Manso, Rob J. Hyndman
In particular, global linear models can provide competitive accuracy with two orders of magnitude fewer parameters than local methods.