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» Dynamic Histograms: Capturing Evolving Data Sets
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ICCV
2007
IEEE
14 years 9 months ago
DynamicBoost: Boosting Time Series Generated by Dynamical Systems
Boosting is a remarkably simple and flexible classification algorithm with widespread applications in computer vision. However, the application of boosting to nonEuclidean, infini...
René Vidal, Paolo Favaro
FAST
2009
13 years 5 months ago
Provenance as Data Mining: Combining File System Metadata with Content Analysis
Provenance describes how an object came to be in its present state. Thus, it describes the evolution of the object over time. Prior work on provenance has focussed on databases an...
Vinay Deolalikar, Hernan Laffitte
SEMWEB
2010
Springer
13 years 5 months ago
Summary Models for Routing Keywords to Linked Data Sources
The proliferation of linked data on the Web paves the way to a new generation of applications that exploit heterogeneous data from different sources. However, because this Web of d...
Thanh Tran, Lei Zhang, Rudi Studer
MLDM
2005
Springer
14 years 1 months ago
Clustering Large Dynamic Datasets Using Exemplar Points
In this paper we present a method to cluster large datasets that change over time using incremental learning techniques. The approach is based on the dynamic representation of clus...
William Sia, Mihai M. Lazarescu
AUSDM
2008
Springer
225views Data Mining» more  AUSDM 2008»
13 years 9 months ago
Evaluation of Malware clustering based on its dynamic behaviour
Malware detection is an important problem today. New malware appears every day and in order to be able to detect it, it is important to recognize families of existing malware. Dat...
Ibai Gurrutxaga, Olatz Arbelaitz, Jesús M. ...