Compressed Sensing and Its Applications: Third International MATHEON Conference 2017

by Holger Boche (Editor), Giuseppe Caire (Editor), Robert Calderbank (Editor), Gitta Kutyniok (Editor), Rudolf Mathar (Editor)

Overview

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.

Product Details

ISBN-13:	9783319730745
Publisher:	Birkhäuser
Publication date:	08/13/2019
Series:	Applied and Numerical Harmonic Analysis
Sold by:	Barnes & Noble
Format:	eBook
File size:	34 MB
Note:	This product may take a few minutes to download.

Table of Contents

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.