47 search results - page 3 / 10 » Approximate Marginals in Latent Gaussian Models |
ICML
2008
IEEE
14 years 7 months ago
2008
IEEE
Stationarity is often an unrealistic prior assumption for Gaussian process regression. One solution is to predefine an explicit nonstationary covariance function, but such covaria...
UAI
2008
13 years 7 months ago
2008
We address the problem of computing approximate marginals in Gaussian probabilistic models by using mean field and fractional Bethe approximations. As an extension of Welling and ...
TIP
2008
13 years 6 months ago
2008
This paper presents recursive cavity modeling--a principled, tractable approach to approximate, near-optimal inference for large Gauss-Markov random fields. The main idea is to su...
JMLR
2012
11 years 8 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...
ICML
2010
IEEE
13 years 7 months ago
2010
IEEE
This paper proposes a multiple instance learning (MIL) algorithm for Gaussian processes (GP). The GP-MIL model inherits two crucial benefits from GP: (i) a principle manner of lea...