Ranked sparsity: a regularization framework for selecting features in the presence of prior informational asymmetry
In this dissertation, we explore and illustrate the concept of ranked sparsity, a phenomenon that often occurs naturally in the presence of derived variables. Ranked sparsity arises in modeling applications when an expected disparity exists in the quality of information between different feature set...
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| Format: | Others |
| Language: | English |
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University of Iowa
2019
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| Online Access: | https://ir.uiowa.edu/etd/6834 https://ir.uiowa.edu/cgi/viewcontent.cgi?article=8368&context=etd |