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ARC Code TI: Block-GP: Scalable Gaussian Process Regression
Block GP is a Gaussian Process regression framework for multimodal data, that can be an order of magnitude more scalable than existing state-of-the-art nonlinear regression algorithms. The framework builds local Gaussian Processes on semantically meaningful partitions of the data and provides higher prediction accuracy than a single global model with very high confidence.
Complete Metadata
| bureauCode |
[ "026:00" ] |
|---|---|
| identifier | OCIO-Fitara-113 |
| issued | 2015-07-21 |
| landingPage | http://ti.arc.nasa.gov/opensource/projects/block-gp/ |
| programCode |
[ "026:046" ] |
| theme |
[ "Management/Operations" ] |
