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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 ...
Interpretability of deep learning models: a survey of results
(IEEE, 2018-06-26)
Deep neural networks have achieved near-human accuracy levels in various types of classification and prediction tasks including images, text, speech, and video data. However, the networks continue to be treated mostly as ...
A generalized stereotype learning approach and its instantiation in trust modeling
(Elsevier, 2018-08)
Owing to the lack of historical data regarding an entity in online communities, a user may rely on stereotyping to estimate its behavior based on historical data about others. However, these stereotypes cannot accurately ...
On context-aware DDoS attacks using deep generative networks
(IEEE, 2018-10)
Distributed Denial of Service (DDoS) attacks continue to be one of the most severe threats in the Internet. The intrinsic challenge in preventing DDoS attacks is to distinguish them from legitimate flash crowds since two ...
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 ...
Combining semantic web and IoT to reason with health and safety policies
(IEEE, 2018-01-12)
Monitoring and following health and safety regulations are especially important - but made difficult - in hazardous work environments such as underground mines to prevent work place accidents and illnesses. Even though ...
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