Bayesian Mixed-Membership Models of Complex and Evolving Networks
CARNEGIE-MELLON UNIV PITTSBURGH PA SCHOOL OF COMPUTER SCIENCE
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This thesis provides a methodological framework for the statistical analysis of complex graphs and dynamic networks.1 In it, I develop probabilistic algorithms that generate, evolve and integrate a heterogeneous collection of graphs, I study the statistical models these algorithms implicitly specify, and I develop strategies for estimating the set of quantities on which they depend in the context of applications to social and biological networks.
- Computer Systems