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Compressed Sensing and Its Applications

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Cover of 'Compressed Sensing and Its Applications'

Table of Contents

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    Book Overview
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    Chapter 1 An Introduction to Compressed Sensing
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    Chapter 2 Quantized Compressed Sensing: A Survey
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    Chapter 3 On Reconstructing Functions from Binary Measurements
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    Chapter 4 Classification Scheme for Binary Data with Extensions
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    Chapter 5 Generalization Error in Deep Learning
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    Chapter 6 Deep Learning for Trivial Inverse Problems
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    Chapter 7 Oracle Inequalities for Local and Global Empirical Risk Minimizers
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    Chapter 8 Median-Truncated Gradient Descent: A Robust and Scalable Nonconvex Approach for Signal Estimation
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    Chapter 9 Reconstruction Methods in THz Single-Pixel Imaging
Attention for Chapter 4: Classification Scheme for Binary Data with Extensions
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