Good Initializations of Variational Bayes for Deep Models

18 Oct 2018Simone RossiPietro MichiardiMaurizio Filippone

Stochastic variational inference is an established way to carry out approximate Bayesian inference for deep models. While there have been effective proposals for good initializations for loss minimization in deep learning, far less attention has been devoted to the issue of initialization of stochastic variational inference... (read more)

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