Maximum Margin Clustering Linli Xu y James Neufeld Bryce Larson Dale Schuurmans University of Waterloo University of Alberta Abstract We propose a new method for clustering based on nding maximum mar
By reformulating the problem in terms of the implied equivalence relation matrix we can pose the problem as a convex integer program Although this still yields a dif64257cult com putational problem the hardclustering constraints can be relaxed to a
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