Processing Multiple Distortion Models: A Comparative Study
Abstract
When dealing with uncertain information, distortion or neighbourhood models are convenient practical tools, as they rely on very few parameters. In this paper, we study their behaviour when such models are combined and processed. More specifically, we study their behaviour when merging different distortion models quantifying uncertainty on the same quantity, and when manipulating distortion models defined over multiple variables.
Cite
Text
Destercke et al. "Processing Multiple Distortion Models: A Comparative Study." Proceedings of the Twelveth International Symposium on Imprecise Probability: Theories and Applications, 2021.Markdown
[Destercke et al. "Processing Multiple Distortion Models: A Comparative Study." Proceedings of the Twelveth International Symposium on Imprecise Probability: Theories and Applications, 2021.](https://mlanthology.org/isipta/2021/destercke2021isipta-processing/)BibTeX
@inproceedings{destercke2021isipta-processing,
title = {{Processing Multiple Distortion Models: A Comparative Study}},
author = {Destercke, Sébastien and Montes, Ignacio and Miranda, Enrique},
booktitle = {Proceedings of the Twelveth International Symposium on Imprecise Probability: Theories and Applications},
year = {2021},
pages = {122-131},
volume = {147},
url = {https://mlanthology.org/isipta/2021/destercke2021isipta-processing/}
}