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» Bayesian Approaches to Gaussian Mixture Modeling
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ICML
2005
IEEE
14 years 9 months ago
Preference learning with Gaussian processes
In this paper, we propose a probabilistic kernel approach to preference learning based on Gaussian processes. A new likelihood function is proposed to capture the preference relat...
Wei Chu, Zoubin Ghahramani
PKDD
2009
Springer
92views Data Mining» more  PKDD 2009»
14 years 3 months ago
A Generic Approach to Topic Models
This article contributes a generic model of topic models. To define the problem space, general characteristics for this class of models are derived, which give rise to a represent...
Gregor Heinrich
CSL
2006
Springer
13 years 9 months ago
Product of Gaussians for speech recognition
Recently there has been interest in the use of classifiers based on the product of experts (PoE) framework. PoEs offer an alternative to the standard mixture of experts (MoE) fram...
M. J. F. Gales, S. S. Airey
DAGM
2009
Springer
14 years 3 months ago
Localised Mixture Models in Region-Based Tracking
An important problem in many computer vision tasks is the separation of an object from its background. One common strategy is to estimate appearance models of the object and backgr...
Christian Schmaltz, Bodo Rosenhahn, Thomas Brox, J...
ECSQARU
2005
Springer
14 years 2 months ago
Nonlinear Deterministic Relationships in Bayesian Networks
In a Bayesian network with continuous variables containing a variable(s) that is a conditionally deterministic function of its continuous parents, the joint density function for t...
Barry R. Cobb, Prakash P. Shenoy