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FGCS
2007
78views more  FGCS 2007»
13 years 7 months ago
Promoting performance and separation of concerns for data mining applications on the grid
Grid Computing brought the promise of making high-performance computing cheaper and more easily available than traditional supercomputing platforms. Such a promise was very well r...
Vasco Furtado, Francisco Flávio de Souza, W...
INFOCOM
2010
IEEE
13 years 6 months ago
Tracking Quantiles of Network Data Streams with Dynamic Operations
— Quantiles are very useful in characterizing the data distribution of an evolving dataset in the process of data mining or network monitoring. The method of Stochastic Approxima...
Jin Cao, Li (Erran) Li, Aiyou Chen, Tian Bu
AAAI
2010
13 years 9 months ago
Constraint Programming for Data Mining and Machine Learning
Machine learning and data mining have become aware that using constraints when learning patterns and rules can be very useful. To this end, a large number of special purpose syste...
Luc De Raedt, Tias Guns, Siegfried Nijssen
ICDM
2005
IEEE
148views Data Mining» more  ICDM 2005»
14 years 1 months ago
Online Hierarchical Clustering in a Data Warehouse Environment
Many important industrial applications rely on data mining methods to uncover patterns and trends in large data warehouse environments. Since a data warehouse is typically updated...
Elke Achtert, Christian Böhm, Hans-Peter Krie...
SDM
2008
SIAM
206views Data Mining» more  SDM 2008»
13 years 9 months ago
Latent Variable Mining with Its Applications to Anomalous Behavior Detection
In this paper, we propose a new approach to anomaly detection by looking at the latent variable space to make the first step toward latent anomaly detection. Most conventional app...
Shunsuke Hirose, Kenji Yamanishi