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Thesis

Task-oriented learning of structured probability distributions

Abstract:

Machine learning models automatically learn from historical data to predict unseen events. Such events are often represented as complex multi-dimensional structures. In many cases there is high uncertainty in the prediction process. Research has developed probabilistic models to capture distributions of complex objects, but their learning objective is often agnostic of the evaluation loss. In this thesis, we address the aforementioned defficiency by designing probabilistic methods for...

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Division:
MPLS
Department:
Engineering Science
Role:
Author

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Role:
Supervisor
Role:
Supervisor
Microsoft Research Cambridge More from this funder
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford
Subjects:
UUID:
uuid:0665495b-afbb-483b-8bdf-cbc6ae5baeff
Deposit date:
2018-04-18

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