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 k-means and ratio-cut


Review for NeurIPS paper: Efficient Clustering Based On A Unified View Of K-means And Ratio-cut

Neural Information Processing Systems

Additional Feedback: EDIT: I am satisfied by the response of the reviewers that they will address the issues of clarity, after which I believe the paper represents a valuable contribution. I commend the authors for what appears to be an innovative algorithm with extremely good practical performance. I believe the paper could be a very influential one, but I feel the presentation of the work needs to be modified and improved. I think there are a few too many concessions which are made. For example, you begin with ratio cut, then change to normalised cut when you assert that the affinity matrix is made doubly stochastic.


Review for NeurIPS paper: Efficient Clustering Based On A Unified View Of K-means And Ratio-cut

Neural Information Processing Systems

The authors present an efficient algorithm for the sum-of-square objective. The proposed method has very impressive experimental performances and could be of interest for a broad audience. The paper contains a number of typos that should be fixed before publication.