Recently, there has been an increased focus on modeling uncertainty by distributions. Suppose we wish to compute a function of a stream whose elements are samples drawn independen...
We present a fast algorithm for computing approximate quantiles in high speed data streams with deterministic error bounds. For data streams of size N where N is unknown in advanc...
— Quantiles are very useful in characterizing the data distribution of an evolving dataset in the process of data mining or network monitoring. The method of Stochastic Approxima...
While traditional database systems optimize for performance on one-shot queries, emerging large-scale monitoring applications require continuous tracking of complex aggregates and...
Graham Cormode, Minos N. Garofalakis, S. Muthukris...
In a recent paper, Ajtai et al. [1] give a streaming algorithm to count the number of inversions in a stream Ä ¾ Ñ Ò using two passes and Ç´¯ ½ ÔÒÐÓ Ò´ÐÓ Ñ·ÐÓ...