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Iterative Subsampling in Solution Path Clustering of Noisy Big Data
We develop an iterative subsampling approach to improve the computational efficiency of our previous work on solution path clustering (SPC).
Solution Path Clustering with Adaptive Concave Penalty
Fast accumulation of large amounts of complex data has created a need for more sophisticated statistical methodologies to discover interesting patterns and better extract information from these data.
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