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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 modeling, focusing on its applications in fields including neuroscience, computational biology, and comput…
- Edition
- -
- ISBN/ISSN
- 9780262325325
- Collation
- 1 online resource (xii, 249 pages).
- Series Title
- -
- Call Number
- -
Parallelism in Matrix Computations
The book consists of four parts: (I) Basics; (II) Dense and Special Matrix Computations; (III) Sparse Matrix Computations; and (IV) Matrix functions and characteristics. Part I deals with parallel programming paradigms and fundamental kernels, including reordering schemes for sparse matrices. Part II is devoted to dense matrix computations such as parallel algorithms for solving linear systems,…
- Edition
- -
- ISBN/ISSN
- 978-94-017-7188-7
- Collation
- XXX, 473 halaman
- Series Title
- Scientific Computation
- Call Number
- 512.943 4 GAL p
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