Sparse modeling theory, algorithms, and applications

✍ Scribed by Irina Rish, Genady Ya. Grabarnik

Publisher: CRC Press
Year: 2015
Tongue: English
Leaves: 250
Series: Machine Learning & Pattern Recognition Series
Category: Library

No coin nor oath required. For personal study only.

✦ Table of Contents

Cover
Contents
List of Figures
Preface
Chapter 1: Introduction
Chapter 2: Sparse Recovery: Problem Formulations
Chapter 3: Theoretical Results (Deterministic Part)
Chapter 4: Theoretical Results (Probabilistic Part)
Chapter 5: Algorithms for Sparse Recovery Problems
Chapter 6: Beyond LASSO: Structured Sparsity
Chapter 7: Beyond LASSO: Other Loss Functions
Chapter 8: Sparse Graphical Models
Chapter 9: Sparse Matrix Factorization: Dictionary Learning and Beyond
Epilogue
Appendix: Mathematical Background
Bibliography
Color Inserts
Back Cover

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