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Thesis

Efficient algorithms for compressed sensing and matrix completion

Abstract:

Compressed sensing and matrix completion are two new data acquisition techniques whose efficiency is achieved by exploring low dimensional structures in high dimensional data. Despite the combinatorial nature of compressed sensing and matrix completion, there has been significant development of computationally efficient algorithms which can produce accurate desired solutions to these problems. In this thesis, we are concerned with the development of low per iteration computational com...

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Institution:
University of Oxford
Research group:
Numerical Analysis Group
Oxford college:
St Hilda's College
Department:
Mathematical,Physical & Life Sciences Division
Role:
Author

Contributors

Role:
Supervisor
Publication date:
2014
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
Oxford University, UK
URN:
uuid:0e2e72fb-dd0c-457b-a0a5-f91c5212f5f5
Local pid:
ora:9015

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