Modelling of Parameterized Processes via Regression in the Model Space
Aswolinskiy W, Reinhart F, Steil JJ (2016)
In: Proceedings of 24th European Symposium on Artificial Neural Networks. 53-58.
Konferenzbeitrag
| Veröffentlicht | Englisch
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Einrichtung
Abstract / Bemerkung
We consider the modelling of parameterized processes, where the goal is to model the process for new parameter value combinations. We compare the classical regression approach to a modular approach based on regression in the model space: First, for each process parametrization a model is learned. Second, a mapping from process parameters to model parameters is learned. We evaluate both approaches on a real and a synthetic dataset and show the advantages of the regression in the model space.
Erscheinungsjahr
2016
Titel des Konferenzbandes
Proceedings of 24th European Symposium on Artificial Neural Networks
Seite(n)
53-58
Konferenz
ESANN 2016: European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning
Konferenzort
Brugge
Konferenzdatum
27.04.2016 – 29.04.2016
Page URI
https://pub.uni-bielefeld.de/record/2900970
Zitieren
Aswolinskiy W, Reinhart F, Steil JJ. Modelling of Parameterized Processes via Regression in the Model Space. In: Proceedings of 24th European Symposium on Artificial Neural Networks. 2016: 53-58.
Aswolinskiy, W., Reinhart, F., & Steil, J. J. (2016). Modelling of Parameterized Processes via Regression in the Model Space. Proceedings of 24th European Symposium on Artificial Neural Networks, 53-58.
Aswolinskiy, Witali, Reinhart, Felix, and Steil, Jochen J. 2016. “Modelling of Parameterized Processes via Regression in the Model Space”. In Proceedings of 24th European Symposium on Artificial Neural Networks, 53-58.
Aswolinskiy, W., Reinhart, F., and Steil, J. J. (2016). “Modelling of Parameterized Processes via Regression in the Model Space” in Proceedings of 24th European Symposium on Artificial Neural Networks 53-58.
Aswolinskiy, W., Reinhart, F., & Steil, J.J., 2016. Modelling of Parameterized Processes via Regression in the Model Space. In Proceedings of 24th European Symposium on Artificial Neural Networks. pp. 53-58.
W. Aswolinskiy, F. Reinhart, and J.J. Steil, “Modelling of Parameterized Processes via Regression in the Model Space”, Proceedings of 24th European Symposium on Artificial Neural Networks, 2016, pp.53-58.
Aswolinskiy, W., Reinhart, F., Steil, J.J.: Modelling of Parameterized Processes via Regression in the Model Space. Proceedings of 24th European Symposium on Artificial Neural Networks. p. 53-58. (2016).
Aswolinskiy, Witali, Reinhart, Felix, and Steil, Jochen J. “Modelling of Parameterized Processes via Regression in the Model Space”. Proceedings of 24th European Symposium on Artificial Neural Networks. 2016. 53-58.
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