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198
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KDD
2008
ACM
16 years 7 months ago
2008
ACM
Traditional spectral classification has been proved to be effective in dealing with both labeled and unlabeled data when these data are from the same domain. In many real world ap...
198
Voted
EDBT
2008
ACM
16 years 7 months ago
2008
ACM
Major media companies such as The Financial Times, the Wall Street Journal or Reuters generate huge amounts of textual news data on a daily basis. Mining frequent patterns in this...
217
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ICASSP
2009
IEEE
16 years 2 months ago
2009
IEEE
In this paper, block diagonal linear discriminant analysis (BDLDA) is improved and applied to gene expression data. BDLDA is a classification tool with embedded feature selection...
227
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CVPR
2006
IEEE
16 years 9 months ago
2006
IEEE
We consider the general problem of learning from both labeled and unlabeled data. Given a set of data points, only a few of them are labeled, and the remaining points are unlabele...
207
Voted
UAI
2003
15 years 8 months ago
2003
Methods for learning Bayesian networks can discover dependency structure between observed variables. Although these methods are useful in many applications, they run into computat...