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Title: Change-point estimation in a dynamic stochastic block model Authors:  Monika Bhattacharjee - IIT BOMBAY (India) [presenting]
Moulinath Banerjee - University of Michigan (United States)
George Michailidis - University of Florida (United States)
Abstract: The purpose is to provide an extensive investigation of change-point analysis for networks generated by stochastic block models, to identify key conditions for the consistent estimation of the change-point, and to propose a computationally fast algorithm that solves the problem in many settings that occur in applications. We establish rates of convergence and derive the asymptotic distributions of the change point estimators. The results are illustrated on synthetic data. Finally, it discusses challenges posed by employing clustering algorithms in this problem, that require additional investigation for their full resolution.