Automated Augmented Conjugate Inference for Non-conjugate Gaussian Process Models
Théo Galy-Fajou,
Florian Wenzel,
Manfred Opper
Abstract:We propose automated augmented conjugate inference, a new inference method for nonconjugate Gaussian processes (GP) models. Our method automatically constructs an auxiliary variable augmentation that renders the GP model conditionally conjugate. Building on the conjugate structure of the augmented model, we develop two inference methods. First, a fast and scalable stochastic variational inference method that uses efficient block coordinate ascent updates, which are computed in closed form. Second, an asymptoti… Show more
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