Model selection: Two fundamental measures of coherence and their algorithmic significance

@article{Bajwa2010ModelST,
  title={Model selection: Two fundamental measures of coherence and their algorithmic significance},
  author={Waheed Uz Zaman Bajwa and A. Robert Calderbank and Sina Jafarpour},
  journal={2010 IEEE International Symposium on Information Theory},
  year={2010},
  pages={1568-1572}
}
The problem of model selection arises in a number of contexts, such as compressed sensing, subset selection in linear regression, estimation of structures in graphical models, and signal denoising. This paper generalizes the notion of incoherence in the existing literature on model selection and introduces two fundamental measures of coherence—termed as the worst-case coherence and the average coherence—among the columns of a design matrix. In particular, it utilizes these two measures of… CONTINUE READING
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