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ACL
1998
15 years 8 months ago
Maximum Entropy Model Learning of the Translation Rules
This paper proposes a learning method of translation rules from parallel corpora. This method applies the maximum entropy principle to a probabilistic model of translation rules. ...
Kengo Sato, Masakazu Nakanishi
BMVC
2000
15 years 8 months ago
Region-Based Object Recognition: Pruning Multiple Representations and Hypotheses
We address the problem of object recognition in computer vision. We represent each model and the scene in the form of Attributed Relational Graph. A multiple region representation...
Alireza Ahmadyfard, Josef Kittler
UAI
2003
15 years 8 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
COLING
2000
15 years 8 months ago
Parsing with the Shortest Derivation
Common wisdom has it that tile bias of stochastic grammars in favor of shorter deriwttions of a sentence is hamfful and should be redressed. We show that the common wisdom is wron...
Rens Bod
207
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UAI
1998
15 years 8 months ago
The Bayesian Structural EM Algorithm
In recent years there has been a flurry of works on learning Bayesian networks from data. One of the hard problems in this area is how to effectively learn the structure of a beli...
Nir Friedman