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• W3008519384 abstract "We propose automated augmented conjugate inference, a new inference method for non-conjugate 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 asymptotically correct Gibbs sampler that is useful for small datasets. Our experiments show that our method are up two orders of magnitude faster and more robust than existing state-of-the-art black-box methods." @default.
• W3008519384 created "2020-03-06" @default.
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• W3008519384 date "2020-02-26" @default.
• W3008519384 modified "2023-10-02" @default.
• W3008519384 title "Automated Augmented Conjugate Inference for Non-conjugate Gaussian Process Models" @default.
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• W3008519384 hasPublicationYear "2020" @default.
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