Compressed Sensing and Its Applications: Third International MATHEON Conference 2017 (Applied and Numerical Harmonic Analysis) von Boche, Holger; Caire, Giuseppe; Calderbank, Robert; Kutyniok, Gitta; Mathar, Rudolf; Petersen, Philipp: Very Good Hardcover (2019) 1. Auflage

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Bibliografische Details

Titel: Compressed Sensing and Its Applications: Third International MATHEON Conference 2017 (Applied and Numerical Harmonic Analysis)
Verlag: Birkh�user
Erscheinungsjahr: 2019
Sprache: Englisch
ISBN-10: 3319730738
ISBN-13: 9783319730738
Einband: Hardcover
Auflage: 1. Auflage
Zustand: Very Good

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Inhaltsangabe

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.

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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.

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