Discovering underlying structure from co-occurrence data is an important task in a variety of fields, including: insurance, intelligence, criminal investigation, epidemiology, hu...
Practical clustering algorithms require multiple data scans to achieve convergence. For large databases, these scans become prohibitively expensive. We present a scalable clusteri...
Abstract. Increasingly large multimedia databases in life sciences, ecommerce, or monitoring applications cannot be browsed manually, but require automatic knowledge discovery in d...
The responsiveness of networked applications is limited by communications delays, making network distance an important parameter in optimizing the choice of communications peers. S...
Previous methods of network anomaly detection have focused on defining a temporal model of what is "normal," and flagging the "abnormal" activity that does not...
Kevin M. Carter, Richard Lippmann, Stephen W. Boye...