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PKDD
2009
Springer
144views Data Mining» more  PKDD 2009»
14 years 2 months ago
Compositional Models for Reinforcement Learning
Abstract. Innovations such as optimistic exploration, function approximation, and hierarchical decomposition have helped scale reinforcement learning to more complex environments, ...
Nicholas K. Jong, Peter Stone
ACL
2008
13 years 9 months ago
Bayesian Learning of Non-Compositional Phrases with Synchronous Parsing
We combine the strengths of Bayesian modeling and synchronous grammar in unsupervised learning of basic translation phrase pairs. The structured space of a synchronous grammar is ...
Hao Zhang, Chris Quirk, Robert C. Moore, Daniel Gi...
ICALT
2009
IEEE
13 years 10 months ago
iGLS: Intelligent Grouping for Online Collaborative Learning
One of the factors that affect successful collaborative learning is the composition of collaborative groups. Due to the lack of intelligent grouping according to learners’ pedag...
Shuangyan Liu, Mike Joy, Nathan Griffiths
CAE
2010
13 years 2 months ago
Learning about Shadows from Artists
Renaissance artists discovered methods for imaging realistic depth on a two dimensional surface by re-inventing linear perspective. In solving the problem of depth depiction, they...
Elodie Fourquet
ICCV
2011
IEEE
12 years 7 months ago
The NBNN kernel
Naive Bayes Nearest Neighbor (NBNN) has recently been proposed as a powerful, non-parametric approach for object classification, that manages to achieve remarkably good results t...
Tinne Tuytelaars, Mario Fritz, Kate Saenko, Trevor...