Convex optimization bubeck

  • Why do you need to know convex optimization?

    Convex optimization has become an essential tool in machine learning because many real-world problems can be modeled as convex optimization problems.
    For example, in classification problems, the goal is to find the best hyperplane that separates the data points into different classes..

  • Convex analysis allows for many generalizations to some fundamental results in mathematical finance.
    Convex optimization provides computational possibilities beyond the techniques of stochastic analysis alone. 1.
May 20, 2014Abstract:This monograph presents the main complexity theorems in convex optimization and their corresponding algorithms.
This monograph presents the main complexity theorems in convex optimization and their corresponding algorithms. It begins with the fundamental theory of black-box optimization and proceeds to guide the reader through recent advances in structural Google BooksOriginally published: 2015Author: Sébastien Bubeck

Who wrote a book on convex optimization?

J Renegar

A mathematical view of interior-point methods in convex optimization, volume 3

Siam, 2001 P Richt ́ arik and M Tak ́ ac

Parallel coordinate descent methods for big data optimization

Arxiv preprint arXiv:1212 0873, 2012 H Robbins and S Monro A stochastic approximation method

Annals of Mathematical Statistics, 22:400–407, 1951


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