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.

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Conference Paper | Published | English
Abstract
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.
Publishing Year
Conference
ESANN 2016: European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning
Location
Brugge
Conference Date
27.04.2016 – 29.04.2016
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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, 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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