An Efficient Method for Gradient-Based Adaptation of Hyperparameters in SVM Models

Keerthi, S. S., Sindhwani, Vikas, Chapelle, Olivier

Neural Information Processing Systems 

We consider the task of tuning hyperparameters in SVM models based on minimizing a smooth performance validation function, e.g., smoothed k-fold cross-validation error, using nonlineaI optimization techniques.

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