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1 - Introduction

Published online by Cambridge University Press:  31 March 2022

Stephen J. Wright
Affiliation:
University of Wisconsin, Madison
Benjamin Recht
Affiliation:
University of California, Berkeley
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Summary

In this introductory chapter, we outline the ways in which various problems in data analysis can be formulated as optimization problems. Specifically, we discuss least squares problems, problems in matrix optimization (particularly those involving low-rank matrices), linear and kernel support vector machines, binary and multiclass logistic regression, and deep learning. We also outline the scope of the remainder of the book.

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Publisher: Cambridge University Press
Print publication year: 2022
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  • Introduction
  • Stephen J. Wright, University of Wisconsin, Madison, Benjamin Recht, University of California, Berkeley
  • Book: Optimization for Data Analysis
  • Online publication: 31 March 2022
  • Chapter DOI: https://doi.org/10.1017/9781009004282.002
Available formats
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  • Introduction
  • Stephen J. Wright, University of Wisconsin, Madison, Benjamin Recht, University of California, Berkeley
  • Book: Optimization for Data Analysis
  • Online publication: 31 March 2022
  • Chapter DOI: https://doi.org/10.1017/9781009004282.002
Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • Introduction
  • Stephen J. Wright, University of Wisconsin, Madison, Benjamin Recht, University of California, Berkeley
  • Book: Optimization for Data Analysis
  • Online publication: 31 March 2022
  • Chapter DOI: https://doi.org/10.1017/9781009004282.002
Available formats
×