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NN
1998
Springer
177views Neural Networks» more  NN 1998»
14 years 9 months ago
Soft vector quantization and the EM algorithm
The relation between hard c-means (HCM), fuzzy c-means (FCM), fuzzy learning vector quantization (FLVQ), soft competition scheme (SCS) of Yair et al. (1992) and probabilistic Gaus...
Ethem Alpaydin
PRL
2007
154views more  PRL 2007»
14 years 9 months ago
Regularized mixture discriminant analysis
Abstract – In this paper we seek a Gaussian mixture model (GMM) of the classconditional densities for plug-in Bayes classification. We propose a method for setting the number of ...
Zohar Halbe, Mayer Aladjem
ICML
2003
IEEE
15 years 10 months ago
Bayes Meets Bellman: The Gaussian Process Approach to Temporal Difference Learning
We present a novel Bayesian approach to the problem of value function estimation in continuous state spaces. We define a probabilistic generative model for the value function by i...
Yaakov Engel, Shie Mannor, Ron Meir
ECIR
2009
Springer
15 years 7 months ago
Bayesian Mixture Hierarchies for Automatic Image Annotation
Previous research on automatic image annotation has shown that accurate estimates of the class conditional densities in generative models have a positive effect in annotation perf...
Vassilios Stathopoulos, Joemon M. Jose
IJAR
2006
80views more  IJAR 2006»
14 years 9 months ago
Operations for inference in continuous Bayesian networks with linear deterministic variables
An important class of continuous Bayesian networks are those that have linear conditionally deterministic variables (a variable that is a linear deterministic function of its pare...
Barry R. Cobb, Prakash P. Shenoy