Correlation Clustering and Biclustering With Locally Bounded Errors

@article{Puleo2018CorrelationCA,
  title={Correlation Clustering and Biclustering With Locally Bounded Errors},
  author={Gregory J. Puleo and Olgica Milenkovic},
  journal={IEEE Transactions on Information Theory},
  year={2018},
  volume={64},
  pages={4105-4119}
}
We consider a generalized version of the correlation clustering problem, defined as follows. Given a complete graph <inline-formula> <tex-math notation="LaTeX">$G$ </tex-math></inline-formula> whose edges are labeled with + or −, we wish to partition the graph into clusters while trying to avoid errors: + edges between clusters or − edges within clusters. Classically, one seeks to minimize the total number of such errors. We introduce a new framework that allows the objective to be a more… Expand
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