Sparse modeling theory algorithms de rish irina (26 resultados)

Paperback. Condición: New. Brand new book, sourced directly from publisher. Dispatch time is 7-8 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Hardcover. Condición: As New. 1st Edition. Crisp hardcover, clean pages.

Condición: New.

Condición: As New. Unread book in perfect condition.

Condición: New. pp. 254.

Condición: New.

Condición: New.

Condición: New. pp. 254 1st edition NO-PA16APR2015-KAP.

Paperback / softback. Condición: New. New copy - Usually dispatched within 4 working days.

Condición: As New. Unread book in perfect condition.

Condición: New. pp. 254.

Hardcover. Condición: New. Brand new book, sourced directly from publisher. Dispatch time is 7-8 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Condición: New.

Paperback. Condición: Brand New. 254 pages. 9.25x6.14x0.55 inches. In Stock.

Condición: New.

Condición: New.

Hardback. Condición: New. New copy - Usually dispatched within 4 working days.

Taschenbuch. Condición: Neu. Sparse Modeling | Theory, Algorithms, and Applications | Irina Rish (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2020 | CRC Press | EAN 9780367658922 | Verantwortliche Person für die EU: Taylor and Francis, Taylor & Francis Verlag Gmbh, Kaufingerstr 24, 80331 München, gpsr[at]taylorandfrancis[dot]com | Anbieter: preigu.…

Hardcover. Condición: Brand New. 1st edition. 250 pages. 9.57x6.18x0.83 inches. In Stock.

Paperback. Condición: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Condición: As New. Unread book in perfect condition.

Hardcover. Condición: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Condición: As New. Unread book in perfect condition.

paperback. Condición: New. Paperback. Pub Date: 2018-01-01 Pages: 184 Language: Chinese Publisher: electronic industry press Sparse modeling with close links to the modern statistics. signal processing. machine learning. can realize accurate recovery from a relatively small number of observations be estimated signal. are widely used in image reconstruction. the data of the parameter learning model. fault diagnosis. pattern recognition and thunder.…

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. The book gets you up to speed on the latest sparsity-related developments and will motivate you to continue learning about the field.The authors first present motivating examples and a high-level survey of key recent developments in sparse modeling. The book then describes optimization problems involving commonly used sparsity-enforcing tools, presents essential theoretical results, and discusses several state-of-the-art algorithms for finding sparse solutions. The authors go on to address a variety of sparse recovery problems that extend the basic formulation to more sophisticated forms of structured sparsity and to different loss functions. They also examine a particular class of sparse graphical models and cover dictionary learning and sparse matrix factorizations.…

Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book 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. It describes optimization problems involving commonly used sparsity-enforcing approaches as well as sparse recovery problems that extend the basic formulation to more sophisticated forms of structured sparsity and to different loss functions. The book also covers sparse graphical models, dictionary learning, and sparse matrix factorizations.…