In many application contexts, like statistical databases, scientific databases, query optimizers, OLAP, and so on, data are often summarized into synopses of aggregate values. Su...
Francesco Buccafurri, Filippo Furfaro, Domenico Sa...
Visual data comprises of multi-scale and inhomogeneous signals. In this paper, we exploit these characteristics and develop an adaptive data approximation technique based on a hie...
Clustering constitutes an ubiquitous problem when dealing with huge data sets for data compression, visualization, or preprocessing. Prototype-based neural methods such as neural g...
Alexander Hasenfuss, Barbara Hammer, Fabrice Rossi
Practical clustering algorithms require multiple data scans to achieve convergence. For large databases, these scans become prohibitively expensive. We present a scalable clusteri...
We consider the distributed compression of two (binary memoryless) correlated sources and propose a unique codec that can reach any point in the Slepian-Wolf region. In a previous...