Pure Maths Colloquium: Ngoc Mai Tran

Recursive random partitions in dimension one are staples of Bayesian statistics, with various applications to topics modeling and clustering. Over the last five years, recursive random partitions in higher dimensions have yielded a new class of random forests that are efficient, easy to compute, with good theoretical properties. In particular, there are new, powerful ways to think about recursive random partitions in higher dimensions using stochastic geometry, which promises a lot of future interactions between this field and machine learning.

This talk gives a flavor of the problems, techniques and open questions of interest in this area.