A Generalization Bound for Online Variational Inference

8 Apr 2019Badr-Eddine Chérief-AbdellatifPierre AlquierMohammad Emtiyaz Khan

Bayesian inference provides an attractive online-learning framework to analyze sequential data, and offers generalization guarantees which hold even with model mismatch and adversaries. Unfortunately, exact Bayesian inference is rarely feasible in practice and approximation methods are usually employed, but do such methods preserve the generalization properties of Bayesian inference ?.. (read more)

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