Corpus ID: 4875078

Generalized Concomitant Multi-Task Lasso for Sparse Multimodal Regression

@inproceedings{Massias2017GeneralizedCM,
  title={Generalized Concomitant Multi-Task Lasso for Sparse Multimodal Regression},
  author={Mathurin Massias and Olivier Fercoq and Alexandre Gramfort and Joseph Salmon},
  booktitle={AISTATS},
  year={2017}
}
  • Mathurin Massias, Olivier Fercoq, +1 author Joseph Salmon
  • Published in AISTATS 2017
  • Mathematics, Computer Science
  • In high dimension, it is customary to consider Lasso-type estimators to enforce sparsity. For standard Lasso theory to hold, the regularization parameter should be proportional to the noise level, yet the latter is generally unknown in practice. A possible remedy is to consider estimators, such as the Concomitant/Scaled Lasso, which jointly optimize over the regression coefficients as well as over the noise level, making the choice of the regularization independent of the noise level. However… CONTINUE READING

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