eBook Algorithms for Sparsity-Constrained Optimization, 1st Edition

  • Published By:
  • ISBN-10: 3319018817
  • ISBN-13: 9783319018812
  • DDC: 519.6
  • Grade Level Range: College Freshman - College Senior
  • 107 Pages | eBook
  • Original Copyright 2014 | Published/Released June 2014
  • This publication's content originally published in print form: 2014
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This thesis demonstrates techniques that provide faster and more accurate solutions to a variety of problems in machine learning and signal processing. The author proposes a ’greedy’ algorithm, deriving sparse solutions with guarantees of optimality. The use of this algorithm removes many of the inaccuracies that occurred with the use of previous models.

Table of Contents

Front Cover.
Other Frontmatter.
Other Frontmatter.
Title Page.
Copyright Page.
Supervisor's Foreword.
Parts of This Thesis Have Been Published in the Following Articles.
List of Algorithms.
List of Figures.
List of Tables.
1: Introduction.
2: Preliminaries.
3: Sparsity-Constrained Optimization.
4: 1-Bit Compressed Sensing.
5: Estimation Under Model-Based Sparsity.
6: Projected Gradient Descent for ℓp-Constrained Least Squares.
7: Conclusion and Future Work.
Proofs of Chap. 3.
Proofs of Chap. 4.
Proofs of Chap. 5.
Proofs of Chap. 6.