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» Density Estimation Using Mixtures of Mixtures of Gaussians
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UAI
2003
15 years 7 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
ISM
2008
IEEE
110views Multimedia» more  ISM 2008»
16 years 20 days ago
A Hardware-Independent Fast Logarithm Approximation with Adjustable Accuracy
Many multimedia applications rely on the computation of logarithms, for example, when estimating log-likelihoods for Gaussian Mixture Models. Knowing of the demand to compute loga...
Oriol Vinyals, Gerald Friedland
BMCBI
2007
138views more  BMCBI 2007»
15 years 6 months ago
A full Bayesian hierarchical mixture model for the variance of gene differential expression
Background: In many laboratory-based high throughput microarray experiments, there are very few replicates of gene expression levels. Thus, estimates of gene variances are inaccur...
Samuel O. M. Manda, Rebecca E. Walls, Mark S. Gilt...
ICASSP
2008
IEEE
16 years 22 days ago
Gradient steepness metrics using extended Baum-Welch transformations for universal pattern recognition tasks
In many pattern recognition tasks, given some input data and a family of models, the “best” model is defined as the one which maximizes the likelihood of the data given the m...
Tara N. Sainath, Dimitri Kanevsky, Bhuvana Ramabha...
CVPR
2005
IEEE
16 years 8 months ago
Kernel-Based Bayesian Filtering for Object Tracking
Particle filtering provides a general framework for propagating probability density functions in non-linear and non-Gaussian systems. However, the algorithm is based on a Monte Ca...
Bohyung Han, Ying Zhu, Dorin Comaniciu, Larry S. D...