Data · dataset · 2025
Making Predictions using Large Scale Gaussian Processes
Listed in NASA Data Portal
One of the key problems that arises in many areas is to estimate a potentially nonlinear function [tex] G(x, \theta)[/tex] given input and output samples [tex] ( X,y ) [/tex] so that [tex]y approx G(x, \theta)[/tex].
Description
There are many approaches to addressing this regression problem. Neural networks, regression trees, and many other methods have been developed to estimate [tex]$G$[/tex] given the input output pair [tex] ( X,y ) [/tex].
One method that I have worked with is called Gaussian process regression. There many good texts and papers on the subject. For more technical information on the method and its applications see: gaussianprocess.org/ A key problem that arises in developing these models on very large data sets is that it ends up requiring an [tex]O(N^3)[/tex] computation where N is the number of data points and the training sample.
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Obviously this becomes very problematic when N is large. I discussed this problem with Leslie Foster, a mathematics professor at San Jose State University. He, along with some of his students, developed a method to address this problem based on Cholesky decomposition and pivoting.
He also shows that this leads to a numerically stable result. If ou're interested in some light reading, I’d suggest you take a look at his [recent paper]( ) (which was accepted in the Journal of Machine Learning Research) posted on dashlink. We've also posted code for you to try it out.
Let us know how it goes. If you are interested in applications of this method in the area of prognostics, check out our [new paper](/dashlink/resources/51/) on the subject which was published in IEEE Transactions on Systems, Man, and Cybernetics.
Links
Where it is published
- NASA Data Portal dataset page data.nasa.gov/dataset/making-predictions-using-large-scale-gaussian-processes ↗
landing page · from data nasa gov
Catalogue records · 1
- CKAN API data.nasa.gov/api/3/action/package_show?id=7e0f01b1-8a05-4d4d-9777-fde201455… ↗
metadata API · from data nasa gov
Provenance · 1 source records, 6 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| NASA Data Portal | 7e0f01b1-8a05-4d4d-9777-fde20145519d | 10 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| created_date | source · data nasa gov | connector:data_nasa_gov@1.0.0 | |
| description | source · data nasa gov | connector:data_nasa_gov@1.0.0 | /notes |
| license_text | source · data nasa gov | connector:data_nasa_gov@1.0.0 | |
| publication_date | source · data nasa gov | connector:data_nasa_gov@1.0.0 | |
| title | source · data nasa gov | connector:data_nasa_gov@1.0.0 | /title |
| updated_date | source · data nasa gov | connector:data_nasa_gov@1.0.0 |