There exist emerging applications of data streams that require association rule mining, such
as network traffic monitoring and web click streams analysis. Different from data in traditional …

Sampling has become an integral part of passive network measurement. This role is driven
by the need to control the consumption of resources in the measurement infrastructure under …

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 …

We ask the question: how can Web sites and data aggregators continually release updated
statistics, and meanwhile preserve each individual user's privacy? Suppose we are given a …

We propose an integrated approach for solving both problems of finding the most popular k
elements, and finding frequent elements in a data stream. Our technique is efficient and …

The dynamic and lossy nature of wireless communication poses major challenges to
reliable, self-organizing multihop networks. These non-ideal characteristics are more …

Traditional databases store sets of relatively static records with no pre-defined notion of time,
unless timestamp attributes are explicitly added. While this model adequately represents …

Estimating the frequencies of elements in a data stream is a fundamental task in data
analysis and machine learning. The problem is typically addressed using streaming …

The DRAM substrate is becoming increasingly more vulnerable to Rowhammer as we move
to smaller technology nodes. We introduce ProTRR, the first principled in-DRAM Target Row …

A sketch of a matrix A is another matrix B which is significantly smaller than A but still
approximates it well. Finding such sketches efficiently is an important building block in …