##### 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****************************