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» Inferring Knowledge from a Large Semantic Network
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UAI
2008
15 years 1 months ago
Hybrid Variational/Gibbs Collapsed Inference in Topic Models
Variational Bayesian inference and (collapsed) Gibbs sampling are the two important classes of inference algorithms for Bayesian networks. Both have their advantages and disadvant...
Max Welling, Yee Whye Teh, Bert Kappen
AI
2008
Springer
14 years 10 months ago
MEBN: A language for first-order Bayesian knowledge bases
Although classical first-order logic is the de facto standard logical foundation for artificial intelligence, the lack of a built-in, semantically grounded capability for reasonin...
Kathryn B. Laskey
89
Voted
AAAI
2008
15 years 2 months ago
Knowledge-Based Spatial Reasoning for Scene Generation from Text Descriptions
This system translates basic English descriptions of a wide range of objects in a simplistic zoo environment into plausible, three-dimensional, interactive visualizations of their...
Dan Tappan
CRV
2005
IEEE
208views Robotics» more  CRV 2005»
15 years 5 months ago
Topology Inference for a Vision-Based Sensor Network
In this paper we describe a technique to infer the topology and connectivity information of a network of cameras based on observed motion in the environment. While the technique c...
Dimitri Marinakis, Gregory Dudek
SEMWEB
2010
Springer
14 years 9 months ago
Supporting Natural Language Processing with Background Knowledge: Coreference Resolution Case
Systems based on statistical and machine learning methods have been shown to be extremely effective and scalable for the analysis of large amount of textual data. However, in the r...
Volha Bryl, Claudio Giuliano, Luciano Serafini, Ka...