Hinge loss

In machine learning, the hinge loss is a loss function used for training classifiers. The hinge loss is used for "maximum-margin" classification… (More)
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Highly Cited
2015
Highly Cited
2015
A fundamental challenge in developing high-impact machine learning technologies is balancing the need to model rich, structured… (More)
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Highly Cited
2014
Highly Cited
2014
Traffic sign recognition (TSR) is an important and challenging task for intelligent transportation systems. We describe the… (More)
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2014
2014
Real-time road traffic congestion monitoring is an important and challenging problem. Most existing monitoring approaches require… (More)
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Highly Cited
2013
Highly Cited
2013
Graphical models for structured domains are powerful tools, but the computational complexities of combinatorial prediction spaces… (More)
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2013
2013
Crammer and Singer's method is one of the most popular multiclass support vector machines (SVMs). It considers L1 loss (hinge… (More)
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2011
2011
Multiclass classification is an important and fundamental problem in machine learning. A popular family of multiclass… (More)
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Highly Cited
2008
Highly Cited
2008
We consider the problem of binary classification where the classifier can, for a particular cost, choose not to classify an… (More)
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Highly Cited
2007
Highly Cited
2007
The support vector machine (SVM) has been widely applied for classification problems in both machine learning and statistics… (More)
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Highly Cited
2004
Highly Cited
2004
In this letter, we investigate the impact of choosing different loss functions from the viewpoint of statistical learning theory… (More)
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Highly Cited
1998
Highly Cited
1998
We describe a unifying method for proving relative loss boun ds for online linear threshold classification algorithms, such as th… (More)
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