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» Active Mining in a Distributed Setting
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ALT
2009
Springer
14 years 6 months ago
Average-Case Active Learning with Costs
Abstract. We analyze the expected cost of a greedy active learning algorithm. Our analysis extends previous work to a more general setting in which different queries have differe...
Andrew Guillory, Jeff A. Bilmes
WECWIS
2006
IEEE
78views ECommerce» more  WECWIS 2006»
14 years 3 months ago
Improving Patient Activity Schedules by Multi-agent Pareto Appointment Exchanging
We present a dynamic and distributed approach to the hospital patient scheduling problem: the multi-agent Pareto-improvement appointment exchanging algorithm, MPAEX. It respects t...
Ivan B. Vermeulen, Sander M. Bohte, D. J. A. Somef...
ICDCS
2006
IEEE
14 years 3 months ago
ParRescue: Scalable Parallel Algorithm and Implementation for Biclustering over Large Distributed Datasets
Biclustering refers to simultaneously capturing correlations present among subsets of attributes (columns) and records (rows). It is widely used in data mining applications includ...
Jianhong Zhou, Ashfaq A. Khokhar
SP
1999
IEEE
184views Security Privacy» more  SP 1999»
14 years 2 months ago
A Data Mining Framework for Building Intrusion Detection Models
There is often the need to update an installed Intrusion Detection System (IDS) due to new attack methods or upgraded computing environments. Since many current IDSs are construct...
Wenke Lee, Salvatore J. Stolfo, Kui W. Mok
DEXAW
1998
IEEE
116views Database» more  DEXAW 1998»
14 years 2 months ago
Data-Mining: A Tightly-Coupled Implementation on a Parallel Database Server
Due to the increasingly di culty of discovering patterns in real-world databases using only conventional OLAP tools, an automated process such as data mining is currently essentia...
Mauro Sousa, Marta Mattoso, Nelson F. F. Ebecken