395 search results - page 35 / 79 » Learning to rank with partially-labeled data |
143
Voted
JMLR
2006
15 years 1 months ago
2006
While methods for comparing two learning algorithms on a single data set have been scrutinized for quite some time already, the issue of statistical tests for comparisons of more ...
132
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ICML
2004
IEEE
15 years 7 months ago
2004
IEEE
This paper introduces RankOpt, a linear binary classifier which optimises the area under the ROC curve (the AUC). Unlike standard binary classifiers, RankOpt adopts the AUC stat...
135
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ICML
2004
IEEE
16 years 2 months ago
2004
IEEE
The problem of computing low rank approximations of matrices is considered. The novel aspect of our approach is that the low rank approximations are on a collection of matrices. W...
134
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DOCENG
2006
ACM
15 years 8 months ago
2006
ACM
Category ranking provides a way to classify plain text documents into a pre-determined set of categories. This work proposes to have a look at typical document collections and ana...
ICML
2005
IEEE
16 years 2 months ago
2005
IEEE
Low-rank matrix decompositions are essential tools in the application of kernel methods to large-scale learning problems. These decompositions have generally been treated as black...