Boche / Caire / Calderbank Compressed Sensing and Its Applications

Third International MATHEON Conference 2017
1. Auflage 2019
ISBN: 978-3-319-73074-5
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 295 Seiten, eBook

Reihe: Applied and Numerical Harmonic Analysis

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 sensingClassificationMachine learningOracle inequalitiesNon-convex optimizationImage reconstructionStatistical 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.

Zielgruppe

Research

Autoren/Hrsg.

Boche, Holger

Caire, Giuseppe

Calderbank, Robert

Kutyniok, Gitta

Mathar, Rudolf

Petersen, Philipp

Inhaltsverzeichnis

An Introduction to Compressed Sensing.- Quantized Compressed Sensing: a Survey.- On reconstructing functions from binary measurements.- Classification scheme for binary data with extensions.- Generalization Error in Deep Learning.- Deep learning for trivial inverse problems.- Oracle inequalities for local and global empirical risk minimizers.- Median-Truncated Gradient Descent: A Robust and Scalable Nonconvex Approach for Signal Estimation.- Reconstruction Methods in THz Single-pixel Imaging.