Gradient Descent for Optimization Problems With Sparse Solutions
Sparse modeling is central to many machine learning and signal processing algorithms, because finding a parsimonious model often implicitly removes noise and reveals structure in data. They appear in applications such as feature selection, feature extraction, sparse support vector machines, sparse l...
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| Format: | Others |
| Language: | en |
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Harvard University
2017
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| Online Access: | http://nrs.harvard.edu/urn-3:HUL.InstRepos:33493549 |