Data stream management systems need to control their resources adaptively since stream characteristics and query workload may vary over time. In this paper we investigate an approa...
In this paper we propose a new nonparametric approach to identification of linear time invariant systems using subspace methods. The nonparametric paradigm to prediction of station...
Alessandro Chiuso, Gianluigi Pillonetto, Giuseppe ...
The success of stochastic algorithms is often due to their ability to effectively amplify the performance of search heuristics. This is certainly the case with stochastic sampling ...
We propose a flexible approach for the visualization of large, high-dimensional datasets. The raw, highdimensional data is mapped into an abstract 3D distance space using the Fast...
Recent advances in hardware technology have resulted in the ability to collect and process large amounts of data. In many cases, the collection of the data is a continuous process ...