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» Robust Bayesian Mixture Modelling
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NIPS
2008
13 years 11 months ago
Posterior Consistency of the Silverman g-prior in Bayesian Model Choice
Kernel supervised learning methods can be unified by utilizing the tools from regularization theory. The duality between regularization and prior leads to interpreting regularizat...
Zhihua Zhang, Michael I. Jordan, Dit-Yan Yeung
ICML
2007
IEEE
14 years 10 months ago
Robust mixtures in the presence of measurement errors
We develop a mixture-based approach to robust density modeling and outlier detection for experimental multivariate data that includes measurement error information. Our model is d...
Ata Kabán, Jianyong Sun, Somak Raychaudhury
ICPR
2006
IEEE
14 years 11 months ago
Wavelet denoising of multicomponent images, using a Gaussian Scale Mixture model
In this paper, denoising on multicomponent images is performed. The presented procedure is a spatial waveletbased denoising techniques, based on Bayesian leastsquares optimization...
Paul Scheunders, Steve De Backer
JMLR
2010
169views more  JMLR 2010»
13 years 4 months ago
Matrix-Variate Dirichlet Process Mixture Models
We are concerned with a multivariate response regression problem where the interest is in considering correlations both across response variates and across response samples. In th...
Zhihua Zhang, Guang Dai, Michael I. Jordan
CVPR
2004
IEEE
14 years 12 months ago
Minimum Effective Dimension for Mixtures of Subspaces: A Robust GPCA Algorithm and Its Applications
In this paper, we propose a robust model selection criterion for mixtures of subspaces called minimum effective dimension (MED). Previous information-theoretic model selection cri...
Kun Huang, René Vidal, Yi Ma