Scalable gaussian processes for characterizing multidimensional change surfaces

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...

Podrobná bibliografie
Hlavní autoři:	Herlands, W, Wilson, A, Nickisch, H, Flaxman, S, Neill, D, van Panhuis, W, Xing, E
Médium:	Conference item
Vydáno:	Journal of Machine Learning Research 2016

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