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ICDM
2007
IEEE
14 years 1 months ago
2007
IEEE
The problem of selecting a sample subset sufficient to preserve diversity arises in many applications. One example is in the design of recombinant inbred lines (RIL) for genetic a...
CIKM
2008
Springer
13 years 12 months ago
2008
Springer
Learning a sequence classifier means learning to predict a sequence of output tags based on a set of input data items. For example, recognizing that a handwritten word is "ca...
CIKM
2008
Springer
13 years 12 months ago
2008
Springer
In the past, quite a few fast algorithms have been developed to mine frequent patterns over graph data, with the large spectrum covering many variants of the problem. However, the...
FLAIRS
2004
13 years 11 months ago
2004
Naive Bayes is one of the most efficient and effective inductive learning algorithms for machine learning and data mining. Its competitive performance in classification is surpris...
SIGCOMM
2010
ACM
13 years 10 months ago
2010
ACM
Networks continue to change to support new applications, improve reliability and performance and reduce the operational cost. The changes are made to the network in the form of up...