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» Learning from Logged Implicit Exploration Data
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EMNLP
2008
13 years 10 months ago
Phrase Translation Probabilities with ITG Priors and Smoothing as Learning Objective
The conditional phrase translation probabilities constitute the principal components of phrase-based machine translation systems. These probabilities are estimated using a heurist...
Markos Mylonakis, Khalil Sima'an
NIPS
2008
13 years 10 months ago
Partially Observed Maximum Entropy Discrimination Markov Networks
Learning graphical models with hidden variables can offer semantic insights to complex data and lead to salient structured predictors without relying on expensive, sometime unatta...
Jun Zhu, Eric P. Xing, Bo Zhang
KDD
2005
ACM
168views Data Mining» more  KDD 2005»
14 years 9 months ago
Nomograms for visualizing support vector machines
We propose a simple yet potentially very effective way of visualizing trained support vector machines. Nomograms are an established model visualization technique that can graphica...
Aleks Jakulin, Martin Mozina, Janez Demsar, Ivan B...
PAAPP
2007
109views more  PAAPP 2007»
13 years 8 months ago
Relation rule mining
\Web users are nowadays confronted with the huge variety of available information sources whose content is not targeted at any specific group or layer. Recommendation systems aim...
Mehdi Adda, Rokia Missaoui, Petko Valtchev
ICDM
2010
IEEE
186views Data Mining» more  ICDM 2010»
13 years 6 months ago
MoodCast: Emotion Prediction via Dynamic Continuous Factor Graph Model
Human emotion is one important underlying force affecting and affected by the dynamics of social networks. An interesting question is "can we predict a person's mood base...
Yuan Zhang, Jie Tang, Jimeng Sun, Yiran Chen, Jing...