… from norm estimation is an important step forward in the derandomization of streaming
algorithms, and that our techniques may spur improved derandomizations of other streaming …

… statistics on a data stream subject to the … norms, which are invariant under sign-flips and
coordinate-wise permutations on an input data stream and include Lp norms, k-support norms, …

… estimating cascaded aggregates over a matrix presented as a sequence of updates in a data
stream… We analyze the space complexity of estimating cascaded norms on an n ×d matrix to …

… access to a data stream, which reports individual data points … Using a data stream, how can
we keep count of the number … once without revisiting earlier data in streaming applications. …

… revisit one of the classic problems in the data stream literature, namely, that of estimating …
vector presented as a sequence of additive updates in a stream. It is well-known that using p-…

… While the body of work in data streaming and sketching has made significant contributions,
we argue that this trajectory of crafting special-purpose algorithms is untenable in the long …

… data set, estimating multilevel models can be challenging: the current algorithms used to fit
multilevel models repeatedly revisit all data … revisiting all our stored data points. As a result, all …

… related to data stream management. We will revisit some of these projects in later sections
when we discuss the issues that we are facing in building a general-purpose data stream …

… In each case, we will apply the proposed estimator to a panel data set on the US banking
industry. Data for the study are taken from the Commercial Bank Holding Company Database …