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NIPS
2007
13 years 10 months ago
Bayesian Inference for Spiking Neuron Models with a Sparsity Prior
Generalized linear models are the most commonly used tools to describe the stimulus selectivity of sensory neurons. Here we present a Bayesian treatment of such models. Using the ...
Sebastian Gerwinn, Jakob Macke, Matthias Seeger, M...
NN
2008
Springer
129views Neural Networks» more  NN 2008»
13 years 9 months ago
Neurolinguistic approach to natural language processing with applications to medical text analysis
Brain processes responsible for understanding language are approximated by spreading activation in semantic networks, providing enhanced representations that involve concepts not ...
Wlodzislaw Duch, Pawel Matykiewicz, John Pestian
JDCTA
2010
160views more  JDCTA 2010»
13 years 3 months ago
Learning and Decision Making in Human During a Game of Matching Pennies
To gain insights into the neural basis of such adaptive decision-making processes, we investigated the nature of learning process in humans playing a competitive game with binary ...
Jianfeng Hu, Xiaofeng Li, Jinghai Yin
ICANN
2005
Springer
14 years 2 months ago
Manifold Constrained Variational Mixtures
In many data mining applications, the data manifold is of lower dimension than the dimension of the input space. In this paper, it is proposed to take advantage of this additional ...
Cédric Archambeau, Michel Verleysen
AUSAI
1999
Springer
14 years 1 months ago
Q-Learning in Continuous State and Action Spaces
Abstract. Q-learning can be used to learn a control policy that maximises a scalar reward through interaction with the environment. Qlearning is commonly applied to problems with d...
Chris Gaskett, David Wettergreen, Alexander Zelins...