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» Finding Structure in Reinforcement Learning
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ICML
2009
IEEE
16 years 4 months ago
K-means in space: a radiation sensitivity evaluation
Spacecraft increasingly employ onboard data analysis to inform further data collection and prioritization decisions. However, many spacecraft operate in high-radiation environment...
Kiri L. Wagstaff, Benjamin Bornstein
ICIP
2006
IEEE
16 years 5 months ago
Image Manifold Interpolation using Free-Form Deformations
An important class of image data sets depict an object undergoing deformation. When there are only a few underlying causes of the deformation, these images have a natural lowdimen...
Richard Souvenir, Qilong Zhang, Robert Pless
134
Voted
FLAIRS
2008
15 years 5 months ago
Learning in the Lexical-Grammatical Interface
Children are facile at both discovering word boundaries and using those words to build higher-level structures in tandem. Current research treats lexical acquisition and grammar i...
Tom Armstrong, Tim Oates
132
Voted
ICML
2004
IEEE
16 years 4 months ago
Semi-supervised learning using randomized mincuts
In many application domains there is a large amount of unlabeled data but only a very limited amount of labeled training data. One general approach that has been explored for util...
Avrim Blum, John D. Lafferty, Mugizi Robert Rweban...
150
Voted
BMCBI
2010
229views more  BMCBI 2010»
15 years 3 months ago
Mocapy++ - A toolkit for inference and learning in dynamic Bayesian networks
Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distribut...
Martin Paluszewski, Thomas Hamelryck