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In the streaming model, elements arrive sequentially and can be observed only once. Maintaining statistics and aggregates is an important and non-trivial task in the model. This becomes even more challenging in the sliding windows model, where statistics must be maintained only over the most recent n elements. In their pioneering paper, Datar, Gionis, Indyk and Motwani  presented exponential histograms, an effective method for estimating statistics on sliding windows. In this paper wedoi:10.1109/focs.2007.4389500 fatcat:liojrcq7g5f7rk77o23xh76rti