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B0972
Title: Change point detection for networks with dynamic community structure Authors:  David Choi - Carnegie Mellon University (United States) [presenting]
Abstract: A method is proposed for change point detection in networks that display time-varying community structure, and a bootstrap-based confidence interval to characterize the change in community membership at each change point. To find multiple change points, a simple extension to existing search methods is also proposed, which combines aspects of greedy methods (such as wild binary segmentation) and global optimization by dynamic programming.