Meeting link: https://hausdorff.dm.unipi.it/b/leo-xik-xu4

Title: A tensor method for semi-supervised learning

Semi-supervised learning is the problem of finding clusters in a graph
or a point-clould dataset where we are given "few" initial input labels.
Label Spreading (LS) is a standard technique for this problem, which can
be interpreted as a diffusion process of the labels on the graph. While
there are many variants of LS, nearly all of them are linear models
which, for every node, only account for the information incoming from
its direct neighbors.

Recent work in network science has shown that in many graph algorithms a
great advantage can be obtained when accounting directly for
higher-order features. Such features may be built from the point-cloud
data or the adjac...