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Approximating The Hierarchical Dirichelet Distribution

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This talk is very much a description of work in progress!

The hierarchical Dirichlet distribution is the finite equivalent of the hierarchical Dirichlet process and can be applied to similar problems in language modelling and information retrieval. One such application is sequence prediction, or deciding what comes next given a history of samples. For reasons which I will discuss, it appears reasonable to approximate the predictive distribution using an interpolated n-gram model with update exclusion, but the relationship between the two is not yet fully formalised. In this talk I’ll describe how far I’ve got with this problem and the main issues still to be resolved.

This talk is part of the Inference Group series.

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