|Publication type:||Conference paper|
|Type of review:||Peer review (publication)|
|Title:||An oracle for the optimization of underconstrained compositions of neural networks : the tick hazard use case|
Smits, Theo H. M.
|Proceedings:||Artificial Life and Evolutionary Computation|
|Editors of the parent work:||Schneider, Johannes Josef|
Weyland, Mathias Sebastian
Füchslin, Rudolf Marcel
|Conference details:||XV International Workshop on Artificial Life and Evolutionary Computation (WIVACE), Winterthur, Switzerland, 15-17 September 2021|
|Series:||Communications in Computer and Information Science|
|Publisher / Ed. Institution:||Springer|
|Publisher / Ed. Institution:||Cham|
|Subject (DDC):||006: Special computer methods |
614: Public health and prevention of disease
|Abstract:||Modeling complex real-world variables, such as tick hazard, can face the problem that no measurements are available for the target variable itself. Models developed on the basis of indirect measurements may then lead to an underconstrained problem for which the output cannot be reliably validated. To address such a problem in the tick hazard use case, we propose a novel oracle approach. The goal of the oracle is to generate test scenarios that can be used to test the validity and robustness of our tick hazard model. We report on preliminary results that support the potential of both the model and the oracle approach.|
|Fulltext version:||Published version|
|License (according to publishing contract):||Licence according to publishing contract|
|Departement:||Life Sciences and Facility Management|
|Organisational Unit:||Institute of Computational Life Sciences (ICLS) |
Institute of Natural Resource Sciences (IUNR)
|Published as part of the ZHAW project:||Fighting bites with bytes: Promoting public health with crowdsourced tick prevention|
|Appears in collections:||Publikationen Life Sciences und Facility Management|
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Gygax, G., Ratnaweera, N., Tischhauser, W., Smits, T. H. M., Laube, P., & Ott, T. (2023). An oracle for the optimization of underconstrained compositions of neural networks : the tick hazard use case [Conference paper]. In J. J. Schneider, M. S. Weyland, D. Flumini, & R. M. Füchslin (Eds.), Artificial Life and Evolutionary Computation (pp. 24–31). Springer. https://doi.org/10.1007/978-3-031-23929-8_3
Gygax, G. et al. (2023) ‘An oracle for the optimization of underconstrained compositions of neural networks : the tick hazard use case’, in J.J. Schneider et al. (eds) Artificial Life and Evolutionary Computation. Cham: Springer, pp. 24–31. Available at: https://doi.org/10.1007/978-3-031-23929-8_3.
G. Gygax, N. Ratnaweera, W. Tischhauser, T. H. M. Smits, P. Laube, and T. Ott, “An oracle for the optimization of underconstrained compositions of neural networks : the tick hazard use case,” in Artificial Life and Evolutionary Computation, Jan. 2023, pp. 24–31. doi: 10.1007/978-3-031-23929-8_3.
Gygax, Gregory, et al. “An Oracle for the Optimization of Underconstrained Compositions of Neural Networks : The Tick Hazard Use Case.” Artificial Life and Evolutionary Computation, edited by Johannes Josef Schneider et al., Springer, 2023, pp. 24–31, https://doi.org/10.1007/978-3-031-23929-8_3.
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