Cardinality estimation has a wide range of applications and is of particular importance in
database systems. Various algorithms have been proposed in the past, and the …

A hands-on approach to tasks and techniques in data stream mining and real-time analytics,
with examples in MOA, a popular freely available open-source software framework. Today …

When processing massive data sets, a core task is to construct synopses of the data. To be
useful, a synopsis data structure should be easy to construct while also yielding good …

We introduce a new approach to characterizing the unobserved portion of a distribution,
which provides sublinear--sample estimators achieving arbitrarily small additive constant …

Large-scale genomics demands computational methods that scale sublinearly with the
growth of data. We review several data structures and sketching techniques that have been …

We investigate the adversarial robustness of streaming algorithms. In this context, an
algorithm is considered robust if its performance guarantees hold even if the stream is …

In this paper, we present near-optimal space bounds for Lp-samplers. Given a stream of
updates (additions and subtraction) to the coordinates of an underlying vector x in Rn, a …

Superspreaders (ie, hosts with numerous distinct connections) remain severe threats to
production networks. How to accurately detect superspreaders in real-time at scale remains …

Refactorings are behavior-preserving program transformations that automate design
evolution in object-oriented applications. Three kinds of design evolution are: schema …

We study the mergeability of data summaries. Informally speaking, mergeability requires
that, given two summaries on two datasets, there is a way to merge the two summaries into a …