Rank Selection in Low-rank Matrix Approximations : A Study of Cross-Validation for NMFs

@inproceedings{Kanagal2010RankSI,
  title={Rank Selection in Low-rank Matrix Approximations : A Study of Cross-Validation for NMFs},
  author={Bhargav Kanagal and Vikas Sindhwani},
  year={2010}
}
We consider the problem of model selection in unsupervised statistical learning techniques based on low-rank matrix approximations. While k-fold crossvalidation (CV) has become the standard method of choice for model selection in supervised learning techniques, its adaptation to unsupervised matrix approximation settings has not received sufficient attention in the literature. In this paper, we emphasize the natural link between cross-validating matrix approximations and the task of matrix… CONTINUE READING

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