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» A Bayesian Approach to Semi-Supervised Learning
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PKDD
2010
Springer
168views Data Mining» more  PKDD 2010»
13 years 7 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...
MCS
2005
Springer
14 years 2 months ago
Ensembles of Classifiers from Spatially Disjoint Data
We describe an ensemble learning approach that accurately learns from data that has been partitioned according to the arbitrary spatial requirements of a large-scale simulation whe...
Robert E. Banfield, Lawrence O. Hall, Kevin W. Bow...
ICMCS
2005
IEEE
126views Multimedia» more  ICMCS 2005»
14 years 2 months ago
A HMM-Embedded Unsupervised Learning to Musical Event Detection
In this paper, an HMM-embedded unsupervised learning approach is proposed to detect the music events by grouping the similar segments of the music signal. This approach can cluste...
Sheng Gao, Yongwei Zhu
UAI
2001
13 years 10 months ago
Learning the Dimensionality of Hidden Variables
A serious problem in learning probabilistic models is the presence of hidden variables. These variables are not observed, yet interact with several of the observed variables. Dete...
Gal Elidan, Nir Friedman
ITS
2010
Springer
178views Multimedia» more  ITS 2010»
14 years 1 months ago
Learning What Works in ITS from Non-traditional Randomized Controlled Trial Data
The traditional, well established approach to finding out what works in education research is to run a randomized controlled trial (RCT) using a standard pretest and posttest desig...
Zachary A. Pardos, Matthew D. Dailey, Neil T. Heff...