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The purpose of this paper is to propose a solution to an extremely pertinent problem, namely, that of identifying unreliable sensors (in a domain of reliable and unreliable ones) without any knowledge of the ground truth. This fascinating paradox can be formulated in simple terms as trying to identify stochastic liars without any additional information about the truth. Though apparently impossible,...
The fusioning of data from unreliable sensors has received much research attention. The main stream of research assesses the reliability of a sensor by comparing its readings to the ground truth in an online or offline manner. For instance, the Weighted Majority Algorithm is a representative example of a large class of similar legacy algorithms. Recently, some advances have been achieved in identifying...
In many applications, data from different sensors are aggregated in order to obtain more reliable information about the process that the sensors are monitoring. However, the quality of the aggregated information is intricately dependent on the reliability of the individual sensors. In fact, unreliable sensors will tend to report erroneous values of the ground truth, and thus degrade the quality of...
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