The Mondrian Kernel

We introduce the Mondrian kernel, a fast random feature approximation to the Laplace kernel. It is suitable for both batch and online learning, and admits a fast kernel-width-selection procedure as the random features can be re-used efficiently for all kernel widths. The features are constructed by sampling trees via a Mondrian process [Roy and Teh, 2009], and we highlight the connection to Mondrian forests [Lakshminarayanan et al. , 2014], where trees are also sampled via a Mondrian process, but fit independently. This link provides a new insight into the relationship between kernel methods and random forests. 1 Balaji Lakshminarayanan Gatsby Unit University College London

Authors

• Matej Balog
• Balaji Lakshminarayanan
• Zoubin Ghahramani
• Daniel M. Roy 0001
• Yee Whye Teh

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