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AIED
2007
Springer
16 years 22 days ago
Comparing Linguistic Features for Modeling Learning in Computer Tutoring
We compare the relative utility of different automatically computable linguistic feature sets for modeling student learning in computer dialogue tutoring. We use the PARADISE frame...
Katherine Forbes-Riley, Diane J. Litman, Amruta Pu...
GECCO
2005
Springer
158views Optimization» more  GECCO 2005»
16 years 2 days ago
Applying both positive and negative selection to supervised learning for anomaly detection
This paper presents a novel approach of applying both positive selection and negative selection to supervised learning for anomaly detection. It first learns the patterns of the n...
Xiaoshu Hang, Honghua Dai
GECCO
2009
Springer
188views Optimization» more  GECCO 2009»
15 years 10 months ago
Exploiting multiple classifier types with active learning
Many approaches to active learning involve training one classifier by periodically choosing new data points about which the classifier has the least confidence, but designing a co...
Zhenyu Lu, Josh Bongard
SSDBM
1996
IEEE
168views Database» more  SSDBM 1996»
15 years 10 months ago
Data Mining: Machine Learning, Statistics, and Databases
Knowledge discovery in databases and data mining aim at semiautomatic tools for the analysis of large data sets. We give an overview of the area and present someof the research is...
Heikki Mannila
CORR
2010
Springer
76views Education» more  CORR 2010»
15 years 1 months ago
Freezing and Sleeping: Tracking Experts that Learn by Evolving Past Posteriors
A problem posed by Freund is how to efficiently track a small pool of experts out of a much larger set. This problem was solved when Bousquet and Warmuth introduced their mixing p...
Wouter M. Koolen, Tim van Erven