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Recovering Communities via Simulated Annealing

This paper was written for a final project of CS590OP: Numerical Optimization at UMass Amherst. It contains an overview of simulated annealing and attempts to recover Stochastic Block Model parameters via the method.

A Demonstration of the “two-truths” Phenomenon

As a form of unsupervised learning, clustering is an inherently ill-defined problem. Often times a researcher may employ spectral clustering to find the “true” communities in a network, but what if there are two different, yet correct, “truths”?