In real-life temporal scenarios, uncertainty and preferences are often essential, coexisting aspects. We present a formalism where temporal constraints with both preferences and un...
Francesca Rossi, Kristen Brent Venable, Neil Yorke...
Accurate knowledge of the effect of parameter uncertainty on process design and operation is essential for optimal and feasible operation of a process plant. Existing approaches de...
This paper presents a method for estimating uncertainty in MRI-based brain region delineations provided by fully-automated segmentation methods. In large data sets, the uncertainty...
Karl R. Beutner, Gautam Prasad, Evan Fletcher, Cha...
Existing approaches to timing analysis under uncertainty are based on restrictive assumptions. Statistical STA techniques assume that the full probabilistic distribution of parame...
Wei-Shen Wang, Vladik Kreinovich, Michael Orshansk...
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...