Artículo: AMZ-B07L6SNTCL

Sparse Modeling: Theory, Algorithms, and Applications (Chapman & Hall/CRC Machine Learning & Pattern Recognition)

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  • 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 t

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Highlight, take notes, and search in the book In this edition, page numbers are just like the physical edition