[Statlist] Reminder: ETH Young Data Science Researcher Seminar Zurich, Virtual Seminar by Eliza O’Reilly, California Institute of Technology

[Maurer Letizia]

We are glad to announce the following talk in the virtual ETH Young Data Science Researcher Seminar Zurich

"Random Tessellation Features and Forests “  
by Eliza O’Reilly, California Institute of Technology

Time: Thursday, 3 March 2022, 15.00 - 16.00
Place: Zoom at https://ethz.zoom.us/j/62895316484


if you like to join, we meet at ETH Zürich, HG G 19.2, to watch the zoom together 


Abstract: The Mondrian process in machine learning is a recursive partition of space with random axis-aligned cuts used to build random forests and Laplace kernel approximations.  The construction allows for efficient online algorithms, but the restriction to axis-aligned cuts does not capture dependencies between features. By viewing the Mondrian as a special case of the stable under iterated (STIT) process in stochastic geometry, we resolve open questions about the generalization of cut directions. We utilize the theory of stationary random tessellations to show that STIT processes approximate a large class of stationary kernels and achieve minimax rates for Lipschitz and C^2 functions. This work opens many new questions at the intersection of stochastic geometry and machine learning. Based on joint work with Ngoc Mai Tran.


M. Azadkia, G. Chinot, J. Hörrmann, M. Löffler, A. Taeb, N. Zhivotovskiy


Please take note of the Covid certificate and mask requirements for joining this lecture. Further details can be found here, https://ethz.ch/services/en/news-and-events/coronavirus.html

Seminar website: https://math.ethz.ch/sfs/news-and-events/young-data-science.html

Young Data Science Researcher Seminar Zurich – Seminar for Statistics | ETH Zurich
math.ethz.ch