Many approaches to active learning involve periodically training one classifier and choosing data points with the lowest confidence. An alternative approach is to periodically cho...
We present a general Multi-Agent System framework for distributed data mining based on a Peer-toPeer model. The framework adopts message-based asynchronous communication and a dyn...
The World Wide Webprovides new opportunities for collecting information from distributed, multiple, and heterogeneous data sources. Information brokering can bc used to provide co...
Heiner Stuckenschmidt, Christoph Schlieder, Ubbo V...
The computing-intensive data mining for inherently Internet-wide distributed data, referred to as Distributed Data Mining (DDM), calls for the support of a powerful Grid with an e...
SMALLbox is a new foundational framework for processing signals, using adaptive sparse structured representations. The main aim of SMALLbox is to become a test ground for explorati...
Ivan Damnjanovic, Matthew E. P. Davies, Mark D. Pl...