Weighted Theta Functions and Embeddings with Applications to Max-Cut, Clustering and Summarization

@inproceedings{Johansson2015WeightedTF,
  title={Weighted Theta Functions and Embeddings with Applications to Max-Cut, Clustering and Summarization},
  author={Fredrik D. Johansson and Ankani Chattoraj and Chiranjib Bhattacharyya and Devdatt P. Dubhashi},
  booktitle={NIPS},
  year={2015}
}
We introduce a unifying generalization of the Lovász theta function, and the associated geometric embedding, for graphs with weights on both nodes and edges. We show how it can be computed exactly by semidefinite programming, and how to approximate it using SVM computations. We show how the theta function can be interpreted as a measure of diversity in graphs and use this idea, and the graph embedding in algorithms for Max-Cut, correlation clustering and document summarization, all of which are… CONTINUE READING

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