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20 April 2024

» arxiv » 1511.4408

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Scalable Gaussian Processes for Characterizing Multidimensional Change Surfaces
William Herlands ; Andrew Wilson ; Hannes Nickisch ; Seth Flaxman ; Daniel Neill ; Wilbert van Panhuis ; Eric Xing ;
Date:	Fri, 13 Nov 2015 19:38:17 GMT (1841kb,D)
Abstract:	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 flexibly define a change surface in combination with expressive spectral mixture kernels to capture the complex statistical structure. Finally, through the use of novel methods for additive non-separable kernels, we can scale the model to large datasets. We demonstrate the model on numerical and real world data, including a large spatio-temporal disease dataset where we identify previously unknown heterogeneous changes in space and time.
Source:	arXiv, 1511.4408
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