Title:
Recent advances on the reduction and analysis of big and high-dimensional data
Recent advances on the reduction and analysis of big and high-dimensional data
Author(s)
Mak, Simon Tsz Fung
Advisor(s)
Joesph, V. Roshan
Wu, C. F. Jeff
Wu, C. F. Jeff
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Abstract
In an era with remarkable advancements in computer engineering, computational algorithms, and mathematical modeling, data scientists are inevitably faced with the challenge of working with big and high-dimensional data. For many problems, data reduction is a necessary first step; such reduction allows for storage and portability of big data, and enables the computation of expensive downstream quantities. The next step then involves the analysis of big data -- the use of such data for modeling, inference, and prediction. This thesis presents new methods for big data reduction and analysis, with a focus on solving real-world problems in statistics, machine learning and engineering.
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Date Issued
2018-04-06
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Resource Type
Text
Resource Subtype
Dissertation