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» Generation of Attributes for Learning Algorithms
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ICMLA
2009
13 years 6 months ago
Discovering Characterization Rules from Rankings
For many ranking applications we would like to understand not only which items are top-ranked, but also why they are top-ranked. However, many of the best ranking algorithms (e.g....
Ansaf Salleb-Aouissi, Bert C. Huang, David L. Walt...
ICML
2009
IEEE
14 years 9 months ago
Herding dynamical weights to learn
A new "herding" algorithm is proposed which directly converts observed moments into a sequence of pseudo-samples. The pseudosamples respect the moment constraints and ma...
Max Welling
ICML
2004
IEEE
14 years 9 months ago
Co-EM support vector learning
Multi-view algorithms, such as co-training and co-EM, utilize unlabeled data when the available attributes can be split into independent and compatible subsets. Co-EM outperforms ...
Ulf Brefeld, Tobias Scheffer
CORR
2010
Springer
74views Education» more  CORR 2010»
13 years 9 months ago
Significance of Classification Techniques in Prediction of Learning Disabilities
The aim of this study is to show the importance of two classification techniques, viz. decision tree and clustering, in prediction of learning disabilities (LD) of school-age chil...
Julie M. David, Kannan Balakrishnan
AAAI
2011
12 years 9 months ago
Quantity Makes Quality: Learning with Partial Views
In many real world applications, the number of examples to learn from is plentiful, but we can only obtain limited information on each individual example. We study the possibiliti...
Nicolò Cesa-Bianchi, Shai Shalev-Shwartz, O...