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173
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EMNLP
2008
15 years 7 months ago
Modeling Annotators: A Generative Approach to Learning from Annotator Rationales
A human annotator can provide hints to a machine learner by highlighting contextual "rationales" for each of his or her annotations (Zaidan et al., 2007). How can one ex...
Omar Zaidan, Jason Eisner
154
Voted
ACL
2012
13 years 8 months ago
Discriminative Pronunciation Modeling: A Large-Margin, Feature-Rich Approach
We address the problem of learning the mapping between words and their possible pronunciations in terms of sub-word units. Most previous approaches have involved generative modeli...
Hao Tang, Joseph Keshet, Karen Livescu
177
Voted
IJCNN
2007
IEEE
16 years 3 days ago
Dynamic Pooling for the Combination of Forecasts generated using Multi Level Learning
— In this paper we provide experimental results and extensions to our previous theoretical findings concerning the combination of forecasts that have been diversified by three ...
Silvia Riedel, Bogdan Gabrys
181
Voted
DIS
2004
Springer
15 years 9 months ago
Generating AVTs Using GA for Learning Decision Tree Classifiers with Missing Data
Abstract. Attribute value taxonomies (AVTs) have been used to perform AVT-guided decision tree learning on partially or totally missing data. In many cases, user-supplied AVTs are ...
Jinu Joo, Jun Zhang 0002, Jihoon Yang, Vasant Hona...
157
Voted
SEAL
2010
Springer
15 years 4 months ago
Generating Sequential Space-Filling Designs Using Genetic Algorithms and Monte Carlo Methods
In this paper, the authors compare a Monte Carlo method and an optimization-based approach using genetic algorithms for sequentially generating space-filling experimental designs....
Karel Crombecq, Tom Dhaene