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Thesis

Numerical algorithms for the mathematics of information

Abstract:

This thesis presents a series of algorithmic innovations in Combinatorial Compressed Sensing and Persistent Homology. The unifying strategy across these contributions is in translating structural patterns in the underlying data into specific algorithmic designs in order to achieve: better guarantees in computational complexity, the ability to operate on more complex data, highly efficient parallelisations, or any combination of these.

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Department:
University of Oxford
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Author

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Department:
University of Oxford
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Supervisor
Department:
University of Oxford
Role:
Examiner
Department:
Duke University
Role:
Examiner
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford

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