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» Learning the Morphological Diversity
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TKDE
2012
226views Formal Methods» more  TKDE 2012»
11 years 10 months ago
DDD: A New Ensemble Approach for Dealing with Concept Drift
—Online learning algorithms often have to operate in the presence of concept drifts. A recent study revealed that different diversity levels in an ensemble of learning machines a...
Leandro L. Minku, Xin Yao
CEC
2010
IEEE
13 years 7 months ago
Behavioral diversity measures for Evolutionary Robotics
Abstract— In Evolutionary Robotics (ER), explicitly rewarding for behavioral diversity recently revealed to generate efficient results without recourse to complex fitness funct...
Stéphane Doncieux, Jean-Baptiste Mouret
DEXAW
2007
IEEE
141views Database» more  DEXAW 2007»
14 years 1 months ago
Automatic Annotation for Korean--Approach Based on the Contextual Exploration Method
We present an automatic semantic annotation system for Korean based on the Contextual Exploration Method. Creating a morphological analyzer and part-of-speech tagger for the Korea...
Hyunzoo Chai
ACL
2011
12 years 11 months ago
Pointwise Prediction for Robust, Adaptable Japanese Morphological Analysis
We present a pointwise approach to Japanese morphological analysis (MA) that ignores structure information during learning and tagging. Despite the lack of structure, it is able t...
Graham Neubig, Yosuke Nakata, Shinsuke Mori
COLT
2003
Springer
14 years 21 days ago
Boosting with Diverse Base Classifiers
Sanjoy Dasgupta, Philip M. Long