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CSDA
2010
208views more  CSDA 2010»
13 years 7 months ago
Bayesian density estimation and model selection using nonparametric hierarchical mixtures
We consider mixtures of parametric densities on the positive reals with a normalized generalized gamma process (Brix, 1999) as mixing measure. This class of mixtures encompasses t...
Raffaele Argiento, Alessandra Guglielmi, Antonio P...
TASLP
2010
157views more  TASLP 2010»
13 years 2 months ago
Multichannel Nonnegative Matrix Factorization in Convolutive Mixtures for Audio Source Separation
Abstract--We consider inference in a general data-driven object-based model of multichannel audio data, assumed generated as a possibly underdetermined convolutive mixture of sourc...
Alexey Ozerov, Cédric Févotte
CSDA
2007
202views more  CSDA 2007»
13 years 7 months ago
Bayesian estimation of the Gaussian mixture GARCH model
In this paper, we perform Bayesian inference and prediction for a GARCH model where the innovations are assumed to follow a mixture of two Gaussian distributions. This GARCH model...
María Concepción Ausín, Pedro...
NIPS
2003
13 years 9 months ago
On the Concentration of Expectation and Approximate Inference in Layered Networks
We present an analysis of concentration-of-expectation phenomena in layered Bayesian networks that use generalized linear models as the local conditional probabilities. This frame...
XuanLong Nguyen, Michael I. Jordan
MICCAI
2008
Springer
14 years 8 months ago
MR Brain Tissue Classification Using an Edge-Preserving Spatially Variant Bayesian Mixture Model
In this paper, a spatially constrained mixture model for the segmentation of MR brain images is presented. The novelty of this work is a new, edge preserving, smoothness prior whic...
Giorgos Sfikas, Christophoros Nikou, Nikolas P. ...