Authors:
- Nominated by Carnegie Mellon University as an outstanding Ph.D. thesis
- Provides an new direction of research into problems of extracting structure from data
- Advances the science of structure discovery through sparsity
- Includes supplementary material: sn.pub/extras
Part of the book series: Springer Theses (Springer Theses, volume 261)
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Table of contents (7 chapters)
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Front Matter
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Back Matter
About this book
Authors and Affiliations
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Carnegie Mellon University, Pittsburgh, USA
Sohail Bahmani
About the author
Bibliographic Information
Book Title: Algorithms for Sparsity-Constrained Optimization
Authors: Sohail Bahmani
Series Title: Springer Theses
DOI: https://doi.org/10.1007/978-3-319-01881-2
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing Switzerland 2014
Hardcover ISBN: 978-3-319-01880-5Published: 18 October 2013
Softcover ISBN: 978-3-319-37719-3Published: 23 August 2016
eBook ISBN: 978-3-319-01881-2Published: 07 October 2013
Series ISSN: 2190-5053
Series E-ISSN: 2190-5061
Edition Number: 1
Number of Pages: XXI, 107
Number of Illustrations: 1 b/w illustrations, 12 illustrations in colour
Topics: Signal, Image and Speech Processing, Mathematical Applications in Computer Science, Image Processing and Computer Vision