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EAAI
2006
123views more  EAAI 2006»
15 years 2 months ago
Imitation learning with spiking neural networks and real-world devices
This article is about a new approach in robotic learning systems. It provides a method to use a real-world device that operates in real-time, controlled through a simulated recurr...
Harald Burgsteiner
HUC
2007
Springer
15 years 8 months ago
How Smart Homes Learn: The Evolution of the Networked Home and Household
Despite a growing desire to create smart homes, we know little about how networked technologies interact with a house’s infrastructure. In this paper, we begin to close this gap ...
Marshini Chetty, Ja-Young Sung, Rebecca E. Grinter
95
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ECML
2005
Springer
15 years 7 months ago
Bayesian Network Learning with Abstraction Hierarchies and Context-Specific Independence
Marie desJardins, Priyang Rathod, Lise Getoor
COLT
1993
Springer
15 years 6 months ago
Lower Bounds on the Vapnik-Chervonenkis Dimension of Multi-Layer Threshold Networks
We consider the problem of learning in multilayer feed-forward networks of linear threshold units. We show that the Vapnik-Chervonenkis dimension of the class of functions that ca...
Peter L. Bartlett
ESANN
2003
15 years 3 months ago
Autonomous learning algorithm for fully connected recurrent networks
In this paper fully connected RTRL neural networks are studied. In order to learn dynamical behaviours of linear-processes or to predict time series, an autonomous learning algori...
Edouard Leclercq, Fabrice Druaux, Dimitri Lefebvre