Privacy-preserving data mining (PPDM) is an emergent research area that addresses the incorporation of privacy preserving concerns to data mining techniques. In this paper we prop...
Learning, planning, and representing knowledge in large state t multiple levels of temporal abstraction are key, long-standing challenges for building flexible autonomous agents. ...
Conventional subspace learning or recent feature extraction methods consider globality as the key criterion to design discriminative algorithms for image classification. We demonst...
Yun Fu, Zhu Li, Junsong Yuan, Ying Wu, Thomas S. H...
In many scientific applications, significant time is spent tuning codes for a particular highperformance architecture. Tuning approaches range from the relatively nonintrusive (...
Albert Hartono, Boyana Norris, Ponnuswamy Sadayapp...
This paper presents a novel networking architecture designed for communication intensive parallel applications running on clusters of workstations (COWs) connected by highspeed ne...
Marcel-Catalin Rosu, Karsten Schwan, Richard Fujim...