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» Learning Internal Representations
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AAAI
2006
15 years 4 months ago
Learning Partially Observable Action Models: Efficient Algorithms
We present tractable, exact algorithms for learning actions' effects and preconditions in partially observable domains. Our algorithms maintain a propositional logical repres...
Dafna Shahaf, Allen Chang, Eyal Amir
127
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IJAR
2006
89views more  IJAR 2006»
15 years 3 months ago
Learning probabilistic decision graphs
Probabilistic decision graphs (PDGs) are a representation language for probability distributions based on binary decision diagrams. PDGs can encode (context-specific) independence...
Manfred Jaeger, Jens D. Nielsen, Tomi Silander
JMLR
2006
104views more  JMLR 2006»
15 years 3 months ago
Learning Image Components for Object Recognition
In order to perform object recognition it is necessary to learn representations of the underlying components of images. Such components correspond to objects, object-parts, or fea...
Michael W. Spratling
JSA
1998
74views more  JSA 1998»
15 years 3 months ago
Windowed active sampling for reliable neural learning
The composition of the example set has a major impact on the quality of neural learning. The popular approach is focused on extensive preprocessing to bridge the representation ga...
Emilia I. Barakova, Lambert Spaanenburg
109
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ACMIDC
2009
15 years 7 months ago
Designing for physical-digital correspondence in tangible learning environments
In tangible learning environments the potential to exploit different physical-digital links increases representational power but also broadens the complexity of design. This paper...
Sara Price, Taciana Pontual Falcão