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» Bayesian Approaches to Gaussian Mixture Modeling
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MLDM
2007
Springer
14 years 3 months ago
Kernel MDL to Determine the Number of Clusters
In this paper we propose a new criterion, based on Minimum Description Length (MDL), to estimate an optimal number of clusters. This criterion, called Kernel MDL (KMDL), is particu...
Ivan O. Kyrgyzov, Olexiy O. Kyrgyzov, Henri Ma&ici...
DSP
2008
13 years 9 months ago
Empirical Bayes linear regression with unknown model order
We study maximum a posteriori probability model order selection for linear regression models, assuming Gaussian distributed noise and coefficient vectors. For the same data model,...
Yngve Selén, Erik G. Larsson
KDD
2006
ACM
201views Data Mining» more  KDD 2006»
14 years 9 months ago
Clustering based large margin classification: a scalable approach using SOCP formulation
This paper presents a novel Second Order Cone Programming (SOCP) formulation for large scale binary classification tasks. Assuming that the class conditional densities are mixture...
J. Saketha Nath, Chiranjib Bhattacharyya, M. Naras...
CSDA
2006
169views more  CSDA 2006»
13 years 9 months ago
Generalized structured additive regression based on Bayesian P-splines
Generalized additive models (GAM) for modelling nonlinear effects of continuous covariates are now well established tools for the applied statistician. In this paper we develop Ba...
Andreas Brezger, Stefan Lang
ISBI
2008
IEEE
14 years 9 months ago
Robust maximum likelihood estimation in Q-space MRI
Q-space imaging is an emerging diffusion weighted MR imaging technique to estimate molecular diffusion probability density functions (PDF's) without the need to assume a Gaus...
Bennett A. Landman, Jonathan A. D. Farrell, Seth A...