Web: http://arxiv.org/abs/2209.07028

Sept. 16, 2022, 1:11 a.m. | Sourav Chatterjee, Mathukumalli Vidyasagar

cs.LG updates on arXiv.org arxiv.org

We consider the problem of estimating the skeleton of a large causal polytree
from a relatively small i.i.d. sample. This is motivated by the problem of
determining causal structure when the number of variables is very large
compared to the sample size, such as in gene regulatory networks. We give an
algorithm that recovers the tree with high accuracy in such settings. The
algorithm works under essentially no distributional or modeling assumptions
other than some mild non-degeneracy conditions.

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