EXPECTATION PROPAGATION IN MIXED MODELS
IAIN JOHNSTONE – STANFORD UNIVERSITY
Matt Wand and colleagues have recently shown that the machine learning technique of expectation propagation (EP) yields state of the art estimation of parameters in generalized linear mixed models. We review this work before asking: are the EP estimators asymptotically efficient? The problem becomes one of defining an appropriate objective function that captures the EP iteration and approximates maximum likelihood well enough to inherit its efficiency. Joint work with the late Peter Hall, Song Mei and Matt Wand.