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In particular , we show that under the standard statistical model for RH , our algorithms are `` statistically consistent '' . Through simulation over a TDMA wireless data network , we show that the parameters of our proposed algorithm can be tuned to speed up the optimization convergence . Second , we show that the loss probability is convex with respect to the service rate . Finally , we show that such temporal segmentation into background and outliers , along with the ranking based on the departure from the background , can be used to generate content summaries of any desired length .