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BC
2002
193views more  BC 2002»
14 years 9 months ago
Resonant spatiotemporal learning in large random recurrent networks
Taking a global analogy with the structure of perceptual biological systems, we present a system composed of two layers of real-valued sigmoidal neurons. The primary layer receives...
Emmanuel Daucé, Mathias Quoy, Bernard Doyon
AIED
2009
Springer
15 years 4 months ago
Detecting the Learning Value of Items In a Randomized Problem Set
Researchers that make tutoring systems would like to know which pieces of educational content are most effective at promoting learning among their students. Randomized controlled e...
Zachary A. Pardos, Neil T. Heffernan
TNN
2008
106views more  TNN 2008»
14 years 9 months ago
Unsupervised Segmentation With Dynamical Units
In this paper, we present a novel network to separate mixtures of inputs that have been previously learned. A significant capability of the network is that it segments the componen...
A. Ravishankar Rao, Guillermo A. Cecchi, Charles C...
ASC
2007
14 years 10 months ago
An approximate stability analysis of nonlinear systems described by Universal Learning Networks
Stability is one of the most important subjects in control systems. As for the stability of nonlinear dynamical systems, Lyapunov’s direct method and linearized stability analys...
Kotaro Hirasawa, Shingo Mabu, Shinji Eto, Jinglu H...
ATAL
2005
Springer
15 years 3 months ago
Agent-organized networks for dynamic team formation
Many multi-agent systems consist of a complex network of autonomous yet interdependent agents. Examples of such networked multi-agent systems include supply chains and sensor netw...
Matthew E. Gaston, Marie desJardins