Scalable gaussian processes for characterizing multidimensional change surfaces
We present a scalable Gaussian process model for identifying and characterizing smooth multidimensional changepoints, and automatically learning changes in expressive covariance structure. We use Random Kitchen Sink features to exibly define a change surface in combination with expressive spectral m...
| Huvudupphovsmän: | , , , , , , |
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| Materialtyp: | Conference item |
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Journal of Machine Learning Research
2016
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