Precision Aggregated Local Models
Large scale Gaussian process (GP) regression is infeasible for larger data sets due to cubic scaling of flops and quadratic storage involved in working with covariance matrices. Remedies in recent literature focus on divide-and-conquer, e.g., partitioning into sub-problems and inducing functional (a...
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Virginia Tech
2021
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| Online Access: | http://hdl.handle.net/10919/102125 |