CUED Publications database

The Mondrian kernel

Balog, M and Lakshminarayanan, B and Ghahramani, Z and Roy, DM and Teh, YW (2016) The Mondrian kernel. 32nd Conference on Uncertainty in Artificial Intelligence 2016, UAI 2016. pp. 32-41.

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Abstract

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.

Item Type: Article
Subjects: UNSPECIFIED
Divisions: Div F > Computational and Biological Learning
Depositing User: Cron Job
Date Deposited: 17 Jul 2017 19:19
Last Modified: 10 Aug 2017 01:39
DOI: