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Department of Mathematics,
Department of Mathematics,
University of California San Diego
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Math 288
Dr. Ludovic Stephan
EPFL
Non-backtracking methods for community detection and beyond
Abstract:
A lot of graph inference problems consist in finding a low-rank structure planted in the adjacency matrix of the graph. When sparse enough, the simple study of the adjacency matrix is not enough; the individual variance of each vertex influences too much the overall spectrum of $A$. In contrast, we show how the non-backtracking matrix $B$ recovers these low-rank structures more consistently. This generalizes the results of Bordenave et al. (2015) to a much wider range of settings, beyond the classical stochastic block model.
November 10, 2022
11:00 AM
Room 6402 with live streaming. Zoom ID: 947 1948 3503. Email poagarwal@ucsd.edu for password
Research Areas
Probability Theory****************************
