Sparse modeling theory, algorithms, and applications
Sparse models are particularly useful in scientific applications, such as biomarker discovery in genetic or neuroimaging data, where the interpretability of a predictive model is essential. Sparsity can also dramatically improve the cost efficiency of signal processing. Sparse Modeling: Theory, Algo...
| Main Authors: | , |
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| Format: | eBook |
| Language: | English |
| Published: |
Boca Raton, FL
CRC Press
2015
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| Series: | Chapman & Hall/CRC machine learning & pattern recognition series
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| Subjects: | |
| Online Access: | |
| Collection: | O'Reilly - Collection details see MPG.ReNa |
| Summary: | Sparse models are particularly useful in scientific applications, such as biomarker discovery in genetic or neuroimaging data, where the interpretability of a predictive model is essential. Sparsity can also dramatically improve the cost efficiency of signal processing. Sparse Modeling: Theory, Algorithms, and Applications provides an introduction to the growing field of sparse modeling, including application examples, problem formulations that yield sparse solutions, algorithms for finding such solutions, and recent theoretical results on sparse recovery |
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| Physical Description: | xviii, 231 pages illustrations (some color) |
| ISBN: | 9781439828700 1439828709 9781322667416 1322667411 1439828695 |