173 search results - page 14 / 35 » Semi-supervised Learning on Directed Graphs |
114
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MOBIHOC
2012
ACM
13 years 2 months ago
2012
ACM
A key feature of wireless communications is the spatial reuse. However, the spatial aspect is not yet well understood for the purpose of designing efficient spectrum sharing mecha...
IJCNN
2006
IEEE
15 years 5 months ago
2006
IEEE
— Recursive Neural Networks (RNNs) and Graph Neural Networks (GNNs) are two connectionist models that can directly process graphs. RNNs and GNNs exploit a similar processing fram...
100
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EUROCOLT
1995
Springer
15 years 3 months ago
1995
Springer
Limiting identification of r.e. indexes for r.e. languages (from a presentation of elements of the language) and limiting identification of programs for computable functions (fr...
112
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JMLR
2010
14 years 6 months ago
2010
Directed acyclic graph (DAG) models are popular tools for describing causal relationships and for guiding attempts to learn them from data. In particular, they appear to supply a ...
134
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KI
2010
Springer
14 years 6 months ago
2010
Springer
In this paper, we address the problem of lifelong map learning in static environments with mobile robots using the graph-based formulation of the simultaneous localization and mapp...