Compressed Sensing and Its Applications

Third International MATHEON Conference 2017

Nonfiction, Science & Nature, Mathematics, Mathematical Analysis, Applied
Cover of the book Compressed Sensing and Its Applications by , Springer International Publishing
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Author: ISBN: 9783319730745
Publisher: Springer International Publishing Publication: August 13, 2019
Imprint: Birkhäuser Language: English
Author:
ISBN: 9783319730745
Publisher: Springer International Publishing
Publication: August 13, 2019
Imprint: Birkhäuser
Language: English

The chapters in this volume highlight the state-of-the-art of compressed sensing and are based on talks given at the third international MATHEON conference on the same topic, held from December 4-8, 2017 at the Technical University in Berlin. In addition to methods in compressed sensing, chapters provide insights into cutting edge applications of deep learning in data science, highlighting the overlapping ideas and methods that connect the fields of compressed sensing and deep learning. Specific topics covered include:

  • Quantized compressed sensing
  • Classification
  • Machine learning
  • Oracle inequalities
  • Non-convex optimization
  • Image reconstruction
  • Statistical learning theory

This volume will be a valuable resource for graduate students and researchers in the areas of mathematics, computer science, and engineering, as well as other applied scientists exploring potential applications of compressed sensing.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

The chapters in this volume highlight the state-of-the-art of compressed sensing and are based on talks given at the third international MATHEON conference on the same topic, held from December 4-8, 2017 at the Technical University in Berlin. In addition to methods in compressed sensing, chapters provide insights into cutting edge applications of deep learning in data science, highlighting the overlapping ideas and methods that connect the fields of compressed sensing and deep learning. Specific topics covered include:

This volume will be a valuable resource for graduate students and researchers in the areas of mathematics, computer science, and engineering, as well as other applied scientists exploring potential applications of compressed sensing.

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