Practical applications of sparse modeling /

"Sparse modeling is a rapidly developing area at the intersection of statistical learning and signal processing, motivated by the age-old statistical problem of selecting a small number of predictive variables in high-dimensional datasets. This collection describes key approaches in sparse mode...

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Bibliographic Details

Other Authors:	Rish, Irina, 1969- (Editor), Cecchi, Guillermo A. (Editor), Lozano, Aurélie Chloé, 1975- (Editor), Niculescu-Mizil, Alexandru (Editor)
Format:	eBook
Language:	English
Published:	Cambridge, Massachusetts : The MIT Press, [2014]
Series:	Neural information processing series
Subjects:	Mathematical models. Sampling (Statistics) Data reduction. Sparse matrices. COMPUTER SCIENCE/Machine Learning & Neural Networks NEUROSCIENCE/General Electronic books.
Online Access:	Connect to the full text of this electronic book