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» Bayesian Hierarchical Mixtures of Experts
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UAI
2003
13 years 6 months ago
Bayesian Hierarchical Mixtures of Experts
The Hierarchical Mixture of Experts (HME) is a well-known tree-structured model for regression and classification, based on soft probabilistic splits of the input space. In its o...
Christopher M. Bishop, Markus Svensén
TMI
2010
182views more  TMI 2010»
13 years 3 months ago
A Bayesian Mixture Approach to Modeling Spatial Activation Patterns in Multisite fMRI Data
Abstract—We propose a probabilistic model for analyzing spatial activation patterns in multiple functional magnetic resonance imaging (fMRI) activation images such as repeated ob...
Seyoung Kim, Padhraic Smyth, Hal S. Stern
JMLR
2010
156views more  JMLR 2010»
12 years 11 months ago
Classification with Incomplete Data Using Dirichlet Process Priors
A non-parametric hierarchical Bayesian framework is developed for designing a classifier, based on a mixture of simple (linear) classifiers. Each simple classifier is termed a loc...
Chunping Wang, Xuejun Liao, Lawrence Carin, David ...
NECO
2002
95views more  NECO 2002»
13 years 4 months ago
Mixture of Experts Classification Using a Hierarchical Mixture Model
Michalis K. Titsias, Aristidis Likas
NIPS
1996
13 years 6 months ago
Adaptively Growing Hierarchical Mixtures of Experts
We propose a novelapproach to automaticallygrowing and pruning Hierarchical Mixtures of Experts. The constructive algorithm proposed here enables large hierarchies consisting of s...
Jürgen Fritsch, Michael Finke, Alex Waibel