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ICANN
2001
Springer
15 years 8 months ago
Learning and Prediction of the Nonlinear Dynamics of Biological Neurons with Support Vector Machines
Based on biological data we examine the ability of Support Vector Machines (SVMs) with gaussian kernels to learn and predict the nonlinear dynamics of single biological neurons. We...
Thomas Frontzek, Thomas Navin Lal, Rolf Eckmiller
CIKM
1995
Springer
15 years 7 months ago
Learning Subjective Relevance to Facilitate Information Access
As the amount of available electronic information is dramatically increasing, the ability for rapid and e ective access to information has become critical. Most traditional inform...
James R. Chen, Nathalie Mathe
APIN
1999
110views more  APIN 1999»
15 years 3 months ago
The Connectionist Inductive Learning and Logic Programming System
The Connectionist Inductive Learning and Logic Programming System, C-IL 2 P, integrates the symbolic and connectionist paradigms of Artificial Intelligence through neural networks...
Artur S. d'Avila Garcez, Gerson Zaverucha
150
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UAI
2008
15 years 5 months ago
Learning Arithmetic Circuits
Graphical models are usually learned without regard to the cost of doing inference with them. As a result, even if a good model is learned, it may perform poorly at prediction, be...
Daniel Lowd, Pedro Domingos
SBRN
2008
IEEE
15 years 10 months ago
Imitation Learning of an Intelligent Navigation System for Mobile Robots Using Reservoir Computing
The design of an autonomous navigation system for mobile robots can be a tough task. Noisy sensors, unstructured environments and unpredictability are among the problems which mus...
Eric A. Antonelo, Benjamin Schrauwen, Dirk Strooba...