Low-rank approximations of the adjacency matrix of a graph are essential in finding patterns (such as communities) and detecting anomalies. Additionally, it is desirable to track ...
Frequent-pattern mining has been studied extensively on scalable methods for mining various kinds of patterns including itemsets, sequences, and graphs. However, the bottleneck of...
In this paper we present an online method for managing a goaloriented buffer partitioning in the distributed memory of a network of workstations. Our algorithm implements a feedba...
Space constrained optimization problems arise in a variety of applications, ranging from databases to ubiquitous computing. Typically, these problems involve selecting a set of it...
Themis Palpanas, Nick Koudas, Alberto O. Mendelzon
In this paper, we propose a new tunable index scheme, called iMinMax(), that maps points in highdimensional spaces to single-dimensional values determined by their maximum or minim...
Cui Yu, Stéphane Bressan, Beng Chin Ooi, Kian-Lee...