171 search results - page 1 / 35 » Factorized Asymptotic Bayesian Inference for Mixture Modelin... |
JMLR
2012
11 years 6 months ago
2012
This paper proposes a novel Bayesian approximation inference method for mixture modeling. Our key idea is to factorize marginal log-likelihood using a variational distribution ove...
AAAI
2010
13 years 5 months ago
2010
Matrix factorization is a fundamental technique in machine learning that is applicable to collaborative filtering, information retrieval and many other areas. In collaborative fil...
CSDA
2010
13 years 4 months ago
2010
A two component parametric mixture is proposed to model survival after an invasive treatment, when patients may experience different hazards regimes: a risk of early mortality dir...
ECML
2006
Springer
13 years 8 months ago
2006
Springer
Abstract. This paper studies a Bayesian framework for density modeling with mixture of exponential family distributions. Variational Bayesian Dirichlet-Multinomial allocation (VBDM...
CORR
2008
Springer
13 years 4 months ago
2008
Springer
Compressive sensing (CS) is an emerging field based on the revelation that a small collection of linear projections of a sparse signal contains enough information for stable, sub-N...