Spatial Analysis Made Easy with Linear Regression and Kernels

22 Feb 2019Philip MiltonEmanuele GiorgiSamir Bhatt

Kernel methods are an incredibly popular technique for extending linear models to non-linear problems via a mapping to an implicit, high-dimensional feature space. While kernel methods are computationally cheaper than an explicit feature mapping, they are still subject to cubic cost on the number of points... (read more)

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