This paper addresses the question: “How can animated visualisation be used to express interesting properties of static analysis?” The particular focus is upon static dependenc...
We consider the problem of maintaining aggregates over recent elements of a massive data stream. Motivated by applications involving network data, we consider asynchronous data str...
Modern scientific applications consume massive volumes of data produced by computer simulations. Such applications require new data management capabilities in order to scale to te...
Learning function relations or understanding structures of data lying in manifolds embedded in huge dimensional Euclidean spaces is an important topic in learning theory. In this ...
We present an evolving neural network model in which synapses appear and disappear stochastically according to bio-inspired probabilities. These are in general nonlinear functions ...