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» Learning with Neural Networks in the Domain of Graphs
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IAT
2008
IEEE
13 years 6 months ago
Scaling Up Multi-agent Reinforcement Learning in Complex Domains
TD-FALCON (Temporal Difference - Fusion Architecture for Learning, COgnition, and Navigation) is a class of self-organizing neural networks that incorporates Temporal Difference (...
Dan Xiao, Ah-Hwee Tan
ICANN
2007
Springer
14 years 12 days ago
Recursive Principal Component Analysis of Graphs
Treatment of general structured information by neural networks is an emerging research topic. Here we show how representations for graphs preserving all the information can be devi...
Alessio Micheli, Alessandro Sperduti
GECCO
2010
Springer
152views Optimization» more  GECCO 2010»
13 years 11 months ago
Importing the computational neuroscience toolbox into neuro-evolution-application to basal ganglia
Neuro-evolution and computational neuroscience are two scientific domains that produce surprisingly different artificial neural networks. Inspired by the “toolbox” used by ...
Jean-Baptiste Mouret, Stéphane Doncieux, Be...
ICANN
2011
Springer
12 years 9 months ago
Transforming Auto-Encoders
The artificial neural networks that are used to recognize shapes typically use one or more layers of learned feature detectors that produce scalar outputs. By contrast, the comput...
Geoffrey E. Hinton, Alex Krizhevsky, Sida D. Wang
IUI
1999
ACM
13 years 10 months ago
Multi-Agent Learning Approach to WWW Information Retrieval Using Neural Network
er has outlined the potential of multiagent framework for decision support. From an abstract point of view, the concept of an agent has been used as modularization principle for th...
Yong S. Choi, Suk I. Yoo