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DATAMINE
1999
108views more  DATAMINE 1999»
14 years 9 months ago
A Survey of Methods for Scaling Up Inductive Algorithms
Abstract. One of the de ning challenges for the KDD research community is to enable inductive learning algorithms to mine very large databases. This paper summarizes, categorizes, ...
Foster J. Provost, Venkateswarlu Kolluri
ACSAC
1999
IEEE
15 years 2 months ago
An Application of Machine Learning to Network Intrusion Detection
Differentiating anomalous network activity from normal network traffic is difficult and tedious. A human analyst must search through vast amounts of data to find anomalous sequenc...
Chris Sinclair, Lyn Pierce, Sara Matzner
TNN
2008
178views more  TNN 2008»
14 years 9 months ago
IMORL: Incremental Multiple-Object Recognition and Localization
This paper proposes an incremental multiple-object recognition and localization (IMORL) method. The objective of IMORL is to adaptively learn multiple interesting objects in an ima...
Haibo He, Sheng Chen
KDD
2007
ACM
191views Data Mining» more  KDD 2007»
15 years 10 months ago
Privacy-Preserving Data Mining through Knowledge Model Sharing
Privacy-preserving data mining (PPDM) is an important topic to both industry and academia. In general there are two approaches to tackling PPDM, one is statistics-based and the oth...
Patrick Sharkey, Hongwei Tian, Weining Zhang, Shou...
ECML
2007
Springer
15 years 3 months ago
On Minimizing the Position Error in Label Ranking
Conventional classification learning allows a classifier to make a one shot decision in order to identify the correct label. However, in many practical applications, the problem ...
Eyke Hüllermeier, Johannes Fürnkranz