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» Probabilistic Explanation Based Learning
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NIPS
2001
13 years 10 months ago
Grammatical Bigrams
Unsupervised learning algorithms have been derived for several statistical models of English grammar, but their computational complexity makes applying them to large data sets int...
Mark A. Paskin
UAI
2003
13 years 10 months ago
The Information Bottleneck EM Algorithm
Learning with hidden variables is a central challenge in probabilistic graphical models that has important implications for many real-life problems. The classical approach is usin...
Gal Elidan, Nir Friedman
ML
2006
ACM
13 years 8 months ago
Using duration models to reduce fragmentation in audio segmentation
We investigate explicit segment duration models in addressing the problem of fragmentation in musical audio segmentation. The resulting probabilistic models are optimised using Mar...
Samer A. Abdallah, Mark B. Sandler, Christophe Rho...
TNN
2010
130views Management» more  TNN 2010»
13 years 3 months ago
Large developing receptive fields using a distributed and locally reprogrammable address-event receiver
A distributed and locally reprogrammable address event receiver has been designed, in which incoming addressevents are monitored simultaneously by all synapses, allowing for arbitr...
Simeon A. Bamford, Alan F. Murray, David J. Willsh...
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...