Meta-learning with neural networks and landmarking for forecasting model selection an empirical evaluation of different feature sets applied to industry data

By Mirko Kück, Sven F. Crone, Michael J. Freitag. 2016

41 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Signal Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Management Science and Operations Research

1. Fotios Petropoulos
2. Rob J Hyndman
3. Konstantinos Nikolopoulos
4. Nikolaos Kourentzes
5. Vassilios Assimakopoulos
6. Spyros Makridakis
7. Evangelos Spiliotis
8. Christoph Bergmeir

In Signal Processing

1. Vassilios Assimakopoulos
2. Konstantinos Nikolopoulos
3. Evangelos Spiliotis
4. Spyros Makridakis
5. Fotios Petropoulos
6. Nikolaos Kourentzes
7. Christoph Bergmeir
8. Devon K. Barrow

Citations in the corpus

• Forecasting: theory and practice (2020, methodology): “Other algorithms such as neural networks and random forecasts are also applied to forecast model selection (Kück et al., 2016; Talagala et al., 2018).”