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» Approximate Marginals in Latent Gaussian Models
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PAMI
2008
145views more  PAMI 2008»
13 years 8 months ago
Latent-Space Variational Bayes
Variational Bayesian Expectation-Maximization (VBEM), an approximate inference method for probabilistic models based on factorizing over latent variables and model parameters, has ...
JaeMo Sung, Zoubin Ghahramani, Sung Yang Bang
SIGPRO
2011
275views Hardware» more  SIGPRO 2011»
12 years 11 months ago
Synthesis of multivariate stationary series with prescribed marginal distributions and covariance using circulant matrix embeddi
The problem of synthesizing multivariate stationary series Y [n] = (Y1[n], . . . , YP [n])T , n ∈ Z, with prescribed non-Gaussian marginal distributions, and a targeted covarian...
Hannes Helgason, Vladas Pipiras, Patrice Abry
JMLR
2010
141views more  JMLR 2010»
13 years 3 months ago
Hierarchical Gaussian Process Regression
We address an approximation method for Gaussian process (GP) regression, where we approximate covariance by a block matrix such that diagonal blocks are calculated exactly while o...
Sunho Park, Seungjin Choi
ICA
2010
Springer
13 years 8 months ago
Probabilistic Latent Tensor Factorization
We develop a probabilistic modeling framework for multiway arrays. Our framework exploits the link between graphical models and tensor factorization models and it can realize any ...
Y. Kenan Yilmaz, A. Taylan Cemgil
ECML
2005
Springer
14 years 2 months ago
U-Likelihood and U-Updating Algorithms: Statistical Inference in Latent Variable Models
Abstract. In this paper we consider latent variable models and introduce a new U-likelihood concept for estimating the distribution over hidden variables. One can derive an estimat...
JaeMo Sung, Sung Yang Bang, Seungjin Choi, Zoubin ...