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ICML
2006
IEEE
16 years 5 months ago
Experience-efficient learning in associative bandit problems
We formalize the associative bandit problem framework introduced by Kaelbling as a learning-theory problem. The learning environment is modeled as a k-armed bandit where arm payof...
Alexander L. Strehl, Chris Mesterharm, Michael L. ...
KDD
2002
ACM
108views Data Mining» more  KDD 2002»
16 years 5 months ago
Incremental Machine Learning to Reduce Biochemistry Lab Costs in the Search for Drug Discovery
This paper promotes the use of supervised machine learning in laboratory settings where chemists have a large number of samples to test for some property, and are interested in id...
George Forman
ICALT
2009
IEEE
15 years 11 months ago
A Graphical Modeling Language for Computer-Based Learning Scenarios
A crucial challenge for improving EMLs is to provide an intuitive notation to support educational practitioners to not only understand, but also describe a large number of flexibl...
Anne Lejeune, Muriel Ney, Armin Weinberger, Margus...
SMC
2007
IEEE
15 years 11 months ago
Enhancing embodied evolution with punctuated anytime learning
—This paper discusses a new implementation of embodied evolution that uses the concept of punctuated anytime learning to increase the complexity of tasks that the learning system...
Gary B. Parker, Gregory E. Fedynyshyn
ICMCS
2006
IEEE
136views Multimedia» more  ICMCS 2006»
15 years 11 months ago
Enhanced Semi-Supervised Learning for Automatic Video Annotation
For automatic semantic annotation of large-scale video database, the insufficiency of labeled training samples is a major obstacle. General semi-supervised learning algorithms can...
Meng Wang, Xian-Sheng Hua, Li-Rong Dai, Yan Song