Computational Methods for Large Spatio-temporal Datasets and Functional Data Ranking
This thesis focuses on two topics, computational methods for large spatial datasets and functional data ranking. Both are tackling the challenges of big and high-dimensional data. The first topic is motivated by the prohibitive computational burden in fitting Gaussian process models to large and ir...
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| Language: | en |
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2017
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| Online Access: | http://hdl.handle.net/10754/625200 http://repository.kaust.edu.sa/kaust/handle/10754/625200 |