We propose a theoretical framework for specification and analysis of a class of learning problems that arise in open-ended environments that contain multiple, distributed, dynamic...
Emerging data stream management systems approach the challenge of massive data distributions which arrive at high speeds while there is only small storage by summarizing and minin...
Traditional methods for data mining typically make the assumption that data is centralized and static. This assumption is no longer tenable. Such methods waste computational and I/...
Adriano Veloso, Matthew Eric Otey, Srinivasan Part...
Dynamically reconfigurable embedded systems offer potential for higher performance as well as adaptability to changing system requirements at low cost. Such systems employ run-tim...
Although distributed object systems, for example RMI and CORBA, enable object-oriented programs to be easily distributed across a network, achieving acceptable performance usually...