Efficient multiple hyperparameter learning for log-linear models

@inproceedings{Do2007EfficientMH,
  title={Efficient multiple hyperparameter learning for log-linear models},
  author={Chuong B. Do and Chuan-Sheng Foo and Andrew Y. Ng},
  booktitle={NIPS},
  year={2007}
}
In problems where input features have varying amounts of noise, using distinct regularization hyperparameters for different features provides an effective means of managing model complexity. While regularizers for neural networks and support vector machines often rely on multiple hyperparameters, regularizers for structured prediction models (used in tasks such as sequence labeling or parsing) typically rely only on a single shared hyperparameter for all features. In this paper, we consider the… CONTINUE READING
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