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Optimization
Overview of attention for book
Table of Contents
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Book Overview
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Chapter 1
Elementary Optimization
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Chapter 2
The Seven C’s of Analysis
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Chapter 3
The Gauge Integral
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Chapter 4
Differentiation
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Chapter 5
Karush-Kuhn-Tucker Theory
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Chapter 6
Convexity
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Chapter 7
Block Relaxation
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Chapter 8
The MM Algorithm
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Chapter 9
The EM Algorithm
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Chapter 10
Newton’s Method and Scoring
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Chapter 11
Conjugate Gradient and Quasi-Newton
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Chapter 12
Analysis of Convergence
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Chapter 13
Penalty and Barrier Methods
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Chapter 14
Convex Calculus
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Chapter 15
Feasibility and Duality
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Chapter 16
Convex Minimization Algorithms
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Chapter 17
The Calculus of Variations
Overall attention for this book and its chapters
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About this Attention Score
Good Attention Score compared to outputs of the same age (75th percentile)
Mentioned by
twitter
1
X user
syllabi
1
institution with syllabi
wikipedia
1
Wikipedia page
Citations
dimensions_citation
132
Dimensions
Book overview
1. Elementary Optimization
2. The Seven C’s of Analysis
3. The Gauge Integral
4. Differentiation
5. Karush-Kuhn-Tucker Theory
6. Convexity
7. Block Relaxation
8. The MM Algorithm
9. The EM Algorithm
10. Newton’s Method and Scoring
11. Conjugate Gradient and Quasi-Newton
12. Analysis of Convergence
13. Penalty and Barrier Methods
14. Convex Calculus
15. Feasibility and Duality
16. Convex Minimization Algorithms
17. The Calculus of Variations
Summary
X
Syllabi
Wikipedia
Dimensions citations
This data is correct as of December 2015 - for more up to date information, please visit
https://opensyllabus.org/
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syllabus from an institution on Open Syllabus Project.
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Course subject areas covered
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Education