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» Learning Hierarchical Performance Knowledge by Observation
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AGI
2008
13 years 9 months ago
Artificial General Intelligence through Large-Scale, Multimodal Bayesian Learning
Abstract. An artificial system that achieves human-level performance on opendomain tasks must have a huge amount of knowledge about the world. We argue that the most feasible way t...
Brian Milch
ECTEL
2006
Springer
13 years 11 months ago
Bayesian Student Models Based on Item to Item Knowledge Structures
Bayesian networks are commonly used in cognitive student modeling and assessment. They typically represent the item-concepts relationships, where items are observable responses to ...
Michel Desmarais, Michel Gagnon
LREC
2010
145views Education» more  LREC 2010»
13 years 9 months ago
Generic Ontology Learners on Application Domains
In ontology learning from texts, we have ontology-rich domains where we have large structured domain knowledge repositories or we have large general corpora with large general str...
Francesca Fallucchi, Maria Teresa Pazienza, Fabio ...
MLMI
2005
Springer
14 years 29 days ago
Hierarchical Multi-stream Posterior Based Speech Recognition System
Abstract. In this paper, we present initial results towards boosting posterior based speech recognition systems by estimating more informative posteriors using multiple streams of ...
Hamed Ketabdar, Hervé Bourlard, Samy Bengio
CVPR
2006
IEEE
14 years 9 months ago
Escaping local minima through hierarchical model selection: Automatic object discovery, segmentation, and tracking in video
Recently, the generative modeling approach to video segmentation has been gaining popularity in the computer vision community. For example, the flexible sprites framework has been...
Nebojsa Jojic, John M. Winn, Larry Zitnick