Various graphs such as web or social networks may contain up to trillions of edges.
Compressing such datasets can accelerate graph processing by reducing the amount of I/O …

How can we find communities in dynamic networks of socialinteractions, such as who calls
whom, who emails whom, or who sells to whom? How can we spot discontinuity time-points …

Nearest neighbor search and many other numerical data analysis tools most often rely on
the use of the euclidean distance. When data are high dimensional, however, the euclidean …

The traveling salesperson (or, salesman) problem (TSP) is a well known and important
combinatorial optimization problem. The goal is to find the shortest tour that visits each city in …

Given a graph with node attributes, how can we find meaningful patterns such as clusters,
bridges, and outliers? Attributed graphs appear in real world in the form of social networks …

Bitmap indexes must be compressed to reduce input/output costs and minimize CPU usage.
To accelerate logical operations (AND, OR, XOR) over bitmaps, we use techniques based …

Column-oriented database systems have been a real game changer for the industry in
recent years. Highly tuned and performant systems have evolved that provide users with the …

Efficient analytics of scientific data from extreme-scale simulations is quickly becoming a top-
notch priority. The increasing simulation output data sizes demand for a paradigm shift in …

Transactional data are ubiquitous. Several methods, including frequent itemset mining and
co-clustering, have been proposed to analyze transactional databases. In this work, we …

Given a matrix of values in which the rows correspond to objects and the columns
correspond to features of the objects, rearrangement clustering is the problem of rearranging …