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Thesis

Collapsed variational inference for computational linguistics

Abstract:

Bayesian modelling is a natural fit for tasks in computational linguistics, since it can provide interpretable structures, useful prior controls, and coherent management of uncertainty. However, exact Bayesian inference is intractable for many models of practical interest. Developing both accurate and efficient approximate Bayesian inference algorithms remains a fundamental challenge, especially for the field of computational linguistics where datasets are large and growing and model...

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Division:
MPLS
Department:
Computer Science
Department:
Computer Science
Role:
Author

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Department:
Computer Science
Role:
Supervisor
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford
UUID:
uuid:13c08f60-1441-4ea5-b52f-7ffd0d7a744f
Deposit date:
2017-06-23

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