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This paper presents a novel pairwise clustering approach. We pose the problem as a question of parameter estimation and show the pairwise indicator variables can be estimated by using the maximum likelihood estimate (MLE) method. Based on this, a two-level clustering algorithm is developed: the grouping graph is first condensed by using the MLE results and then the k-means clustering method is applied...
This paper proposes a sampling based hierarchical approach for solving the computational demands of the spectral clustering methods when applied to the problem of image segmentation. The authors first define the distance between a pixel and a cluster, and then derive a new theorem to estimate the number of samples needed for clustering. Finally, by introducing a scale parameter into the similarity...
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