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IPMU
1992
Springer
15 years 9 months ago
Rule-Based Systems with Unreliable Conditions
This paper deals with the problem of inference under uncertain information. This is a generalization of a paper of Cardona et al. (1991a) where rules were not allowed to contain n...
L. Cardona, Jürg Kohlas, Paul-André Mo...
AAAI
2008
15 years 7 months ago
Hybrid Markov Logic Networks
Markov logic networks (MLNs) combine first-order logic and Markov networks, allowing us to handle the complexity and uncertainty of real-world problems in a single consistent fram...
Jue Wang, Pedro Domingos
NIPS
2008
15 years 6 months ago
Hebbian Learning of Bayes Optimal Decisions
Uncertainty is omnipresent when we perceive or interact with our environment, and the Bayesian framework provides computational methods for dealing with it. Mathematical models fo...
Bernhard Nessler, Michael Pfeiffer, Wolfgang Maass
BC
2007
102views more  BC 2007»
15 years 5 months ago
Bayesian processing of vestibular information
Complex self-motion stimulations in the dark can be powerfully disorienting and can create illusory motion percepts. In the absence of visual cues, the brain has to use angular and...
Jean Laurens, Jacques Droulez
ECCV
2010
Springer
15 years 8 months ago
Automatic Learning of Background Semantics in Generic Surveilled Scenes
Advanced surveillance systems for behavior recognition in outdoor traffic scenes depend strongly on the particular configuration of the scenario. Scene-independent trajectory analy...
Carles Fernández, Jordi Gonzàlez, Xavier Roca