Significant changes in the instance distribution or associated cost function of a learning problem require one to reoptimize a previously-learned classifier to work under new cond...
Chris Bourke, Kun Deng, Stephen D. Scott, Robert E...
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...
In this paper, we assess the impact of heterogeneity on scheduling independent tasks on master-slave platforms. We assume a realistic one-port model where the master can communica...
Pattern classification techniques derived from statistical principles have been widely studied and have proven powerful in addressing practical classification problems. In real-wo...
Pandu Ranga Rao Devarakota, Bruno Mirbach, Bjö...
OLAP is an important tool in decision support. With the help of domain knowledge, such as hierarchies of attribute values, OLAP helps the user observe the effects of various decis...