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139
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ICMLA
2009
15 years 1 months ago
2009
In structured prediction problems, outputs are not confined to binary labels; they are often complex objects such as sequences, trees, or alignments. Support Vector Machine (SVM) ...
156
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JMLR
2012
13 years 6 months ago
2012
We consider the task of devising large-margin based surrogate losses for the learning to rank problem. In this learning to rank setting, the traditional hinge loss for structured ...
165
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ICML
2006
IEEE
16 years 4 months ago
2006
IEEE
There has been much work on applying multiple-instance (MI) learning to contentbased image retrieval (CBIR) where the goal is to rank all images in a known repository using a smal...
168
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JMLR
2002
15 years 3 months ago
2002
Recently, sample complexity bounds have been derived for problems involving linear functions such as neural networks and support vector machines. In many of these theoretical stud...
148
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CORR
2010
Springer
15 years 2 months ago
2010
Springer
This paper proposes a nonparametric Bayesian method for exploratory data analysis and feature construction in continuous time series. Our method focuses on understanding shared fe...