Convex optimization algorithms and complexity pdf

  • What is convex optimization in real world examples?

    Convex optimization has practical applications for the following.

    Portfolio optimization.Worst-case risk analysis.Optimal advertising.Variations of statistical regression (including regularization and quantile regression).Model fitting (particularly multiclass classification).Electricity generation optimization..

  • Training linear regression models is a classic example of a convex optimization problem in which the goal is to find the best-fit line that minimizes the sum of squared errors between the predicted and actual values.

Does convex optimization need a book?

Still the book may not provide all of the convex optimization material an instructor may wish for, and it may need to be supplemented by works that aim primarily at specific types of con- vex optimization models, or address more comprehensively computational complexity issues

What is an abstract convex optimization problem?

Some authors use the term abstract convex optimization problem to describe the (abstract) problem of minimizing a convex function over a convex set

Using this terminology, the problem (4

17) is an abstract convex optimization problem

We will not use this terminology in this book


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