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First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. Stochastic variational inference (SVI) requires careful selection of a step size. This paper proposes a Kalman filter to set the step size automatically. The authors show that standard Gaussian KF does not satisfy the Robbins Munro criteria (and performs badly). They propose to apply a KF based on T-distributions, and show that this gives better results than standard SVI.