47 search results - page 6 / 10 » Compact approximations to Bayesian predictive distributions |
ICML
2008
IEEE
15 years 10 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
14 years 11 months ago
2008
Graphical models are usually learned without regard to the cost of doing inference with them. As a result, even if a good model is learned, it may perform poorly at prediction, be...
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JAIR
2010
14 years 8 months ago
2010
Noisy probabilistic relational rules are a promising world model representation for several reasons. They are compact and generalize over world instantiations. They are usually in...
CORR
2008
Springer
14 years 9 months ago
2008
Springer
Bayesian model averaging, model selection and its approximations such as BIC are generally statistically consistent, but sometimes achieve slower rates of convergence than other m...
ICML
2009
IEEE
15 years 10 months ago
2009
IEEE
We propose an unbounded-depth, hierarchical, Bayesian nonparametric model for discrete sequence data. This model can be estimated from a single training sequence, yet shares stati...