Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization
E. Hüllermeier, International Journal of Approximate Reasoning 55 (2014) 1519–1534.
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International Journal of Approximate Reasoning
Volume
55
Issue
7
Page
1519-1534
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Hüllermeier E. Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization. International Journal of Approximate Reasoning. 2014;55(7):1519-1534.
Hüllermeier, E. (2014). Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization. International Journal of Approximate Reasoning, 55(7), 1519–1534.
@article{Hüllermeier_2014, title={Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization}, volume={55}, number={7}, journal={International Journal of Approximate Reasoning}, author={Hüllermeier, Eyke}, year={2014}, pages={1519–1534} }
Hüllermeier, Eyke. “Learning from Imprecise and Fuzzy Observations: Data Disambiguation through Generalized Loss Minimization.” International Journal of Approximate Reasoning 55, no. 7 (2014): 1519–34.
E. Hüllermeier, “Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization,” International Journal of Approximate Reasoning, vol. 55, no. 7, pp. 1519–1534, 2014.
Hüllermeier, Eyke. “Learning from Imprecise and Fuzzy Observations: Data Disambiguation through Generalized Loss Minimization.” International Journal of Approximate Reasoning, vol. 55, no. 7, 2014, pp. 1519–34.
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