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172
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KDD
2006
ACM
16 years 7 months ago
2006
ACM
Linear Support Vector Machines (SVMs) have become one of the most prominent machine learning techniques for highdimensional sparse data commonly encountered in applications like t...
172
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KDD
2004
ACM
16 years 7 months ago
2004
ACM
Past empirical work has shown that learning multiple related tasks from data simultaneously can be advantageous in terms of predictive performance relative to learning these tasks...
199
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CIDM
2009
IEEE
16 years 1 months ago
2009
IEEE
— Identifying faulty classes in object-oriented software is one of the important software quality assurance activities. This paper empirically investigates the application of t...
172
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PKDD
2009
Springer
16 years 1 months ago
2009
Springer
A serious drawback of kernel methods, and Support Vector Machines (SVM) in particular, is the difficulty in choosing a suitable kernel function for a given dataset. One of the appr...
164
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BIBE
2007
IEEE
16 years 29 days ago
2007
IEEE
—Interactions between transcription factors (TFs) are necessary for deciphering the complex mechanisms of transcription regulation in eukaryotes. In this paper, we proposed a nov...