Sparsity in Machine Learning: Theory and Applications
Sparsity plays a key role in machine learning for several reasons including interpretability. Interpretability is sought either by practitioners or by scientists. Indeed, on one hand interpretability can be key in a practice such as in healthcare, in which black box models cannot be used for the pre...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2022
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| Online Access: | https://hdl.handle.net/1721.1/143157 |