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Selected Applications of Convex Optimization

  • Li Li

Part of the Springer Optimization and Its Applications book series (SOIA, volume 103)

Table of contents

  1. Front Matter
    Pages i-x
  2. Li Li
    Pages 1-15
  3. Li Li
    Pages 17-52
  4. Li Li
    Pages 53-78
  5. Li Li
    Pages 115-126
  6. Li Li
    Pages 127-138
  7. Back Matter
    Pages 139-140

About this book

Introduction

This book focuses on the applications of convex optimization and highlights several topics, including support vector machines, parameter estimation, norm approximation and regularization, semi-definite programming problems, convex relaxation, and geometric problems. All derivation processes are presented in detail to aid in comprehension. The book offers concrete guidance, helping readers recognize and formulate convex optimization problems they might encounter in practice.

Keywords

Convex Optimization Convex Relaxation Expectation Maximization Linear Matrix Inequalities Support Vector Machines data mining

Authors and affiliations

  • Li Li
    • 1
  1. 1.Department of AutomationTsinghua UniversityBeijingChina

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-662-46356-7
  • Copyright Information Tsinghua University Press, Beijing and Springer-Verlag Berlin Heidelberg 2015
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-662-46355-0
  • Online ISBN 978-3-662-46356-7
  • Series Print ISSN 1931-6828
  • Series Online ISSN 1931-6836
  • Buy this book on publisher's site
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