Papers with MetropolisHastings Walker method

1 papers
Scalable Collapsed Inference for High-Dimensional Topic Models (N19-1)

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Challenge: Existing methods have achieved two out of three criteria simultaneously, but never all three at once.
Approach: They propose an online inference algorithm which leverages stochasticity to scale well in the number of documents and sparsity to achieve accurate inference.
Outcome: The proposed algorithm scales well in the number of documents and topics while achieving accurate inference.

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