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» First-order probabilistic inference
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110
Voted
PKDD
2010
Springer
168views Data Mining» more  PKDD 2010»
14 years 11 months ago
Bayesian Knowledge Corroboration with Logical Rules and User Feedback
Current knowledge bases suffer from either low coverage or low accuracy. The underlying hypothesis of this work is that user feedback can greatly improve the quality of automatica...
Gjergji Kasneci, Jurgen Van Gael, Ralf Herbrich, T...
120
Voted
JMLR
2010
145views more  JMLR 2010»
14 years 7 months ago
Parallelizable Sampling of Markov Random Fields
Markov Random Fields (MRFs) are an important class of probabilistic models which are used for density estimation, classification, denoising, and for constructing Deep Belief Netwo...
James Martens, Ilya Sutskever
106
Voted
ECCV
2008
Springer
16 years 2 months ago
Belief Propagation with Directional Statistics for Solving the Shape-from-Shading Problem
The Shape-from-Shading [SfS] problem infers shape from reflected light, collected using a camera at a single point in space only. Reflected light alone does not provide sufficient ...
Tom S. F. Haines, Richard C. Wilson
99
Voted
ICIP
2007
IEEE
16 years 2 months ago
Joint Segmentation and Recognition of License Plate Characters
The segmentation and recognition modules are usually implemented sequentially in most traditional automatic license recognition (LPR) systems. In this work, we integrate segmentat...
Xin Fan, Guoliang Fan, Dequn Liang
ICML
2006
IEEE
16 years 1 months ago
Dynamic topic models
A family of probabilistic time series models is developed to analyze the time evolution of topics in large document collections. The approach is to use state space models on the n...
David M. Blei, John D. Lafferty