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NIPS
2004
14 years 11 months ago
Hierarchical Bayesian Inference in Networks of Spiking Neurons
There is growing evidence from psychophysical and neurophysiological studies that the brain utilizes Bayesian principles for inference and decision making. An important open quest...
Rajesh P. N. Rao
CORR
2008
Springer
129views Education» more  CORR 2008»
14 years 10 months ago
Hierarchical Bayesian sparse image reconstruction with application to MRFM
This paper presents a hierarchical Bayesian model to reconstruct sparse images when the observations are obtained from linear transformations and corrupted by an additive white Gau...
Nicolas Dobigeon, Alfred O. Hero, Jean-Yves Tourne...
RSKT
2007
Springer
15 years 4 months ago
Decision-Theoretic Rough Set Models
Abstract. Decision-theoretic rough set models are a probabilistic extension of the algebraic rough set model. The required parameters for defining probabilistic lower and upper ap...
Yiyu Yao
UM
2005
Springer
15 years 3 months ago
Data-Driven Refinement of a Probabilistic Model of User Affect
We present further developments in our work on using data from real users to build a probabilistic model of user affect based on Dynamic Bayesian Networks (DBNs) and designed to de...
Cristina Conati, Heather Maclaren
ACL
2012
13 years 14 days ago
Improving the IBM Alignment Models Using Variational Bayes
Bayesian approaches have been shown to reduce the amount of overfitting that occurs when running the EM algorithm, by placing prior probabilities on the model parameters. We appl...
Darcey Riley, Daniel Gildea