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Subjective bayesian networks and human-in-the-loop situational understanding
(Springer, 2018-03-21)
In this paper we present a methodology to exploit human-machine coalitions for situational understanding. Situational understanding refers to the ability to relate relevant information and form logical conclusions, as well ...
Trust estimation of sources over correlated propositions
(IEEE, 2018-09-05)
This work analyzes the impact of correlated propositions when estimating the reporting behavior of information sources. These behavior estimates are critical for fusion, and traditional methods assume the propositions are ...
Evidential deep learning to quantify classification uncertainty
(Neural Information Processing Systems Foundation, 2018)
Deterministic neural nets have been shown to learn effective predictors on a wide range of machine learning problems. However, as the standard approach is to train the network to minimize a prediction loss, the resultant ...
Learning and reasoning in complex coalition information environments: a critical analysis
(IEEE, 2018-09-05)
In this paper we provide a critical analysis with metrics that will inform guidelines for designing distributed systems for Collective Situational Understanding (CSU). CSU requires both collective insight - i.e., accurate ...
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