Value Regularization and Fenchel Duality

@article{Rifkin2007ValueRA,
  title={Value Regularization and Fenchel Duality},
  author={Ryan M. Rifkin and Ross Lippert},
  journal={Journal of Machine Learning Research},
  year={2007},
  volume={8},
  pages={441-479}
}
Regularization is an approach to function learning that balances fit and smoothness. In practice, we search for a function f with a finite representation f = ∑i ciφi(·). In most treatments, the ci are the primary objects of study. We consider value regularization, constructing optimization problems in which the predicted values at the training points are the primary variables, and therefore the central objects of study. Although this is a simple change, it has profound consequences. From convex… CONTINUE READING
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