Reviews: Graph Clustering: Block-models and model free results

Neural Information Processing Systems 

The goal is to obtain such guarantees with quantities that can be computed from the data and the output of the clustering algorithms being compared. Providing such model free theoretical guarantees for clustering is of importance for both theoretical and practical purposes. Given that Spectral Clutering works well for all the models specified, why not use the same model estimator? In particular, it is not clear why the Laplacian is used for PFM while the adjacency matrix is used for the SBM. Also, the results for PFM is for weighted ME whereas for SBM it is in terms of ME.