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Abstract:
A new result in the field of variational learning methods is described. Combined with previous work, this completes an algorithm that produces unbiased gradient estimates for learning with variational inference in a large class of models, including some unnormalized models. Depending on time availability, I might also describe a way to do early stopping for some intractable objective functions.