Modern effective methods of convex optimization

Fridays from 10:45 to 12:10, from September 8
Clasroom 430 gk

Course description

An alternative course for 4th-year students in the fall semester from the MOE department.

Instructors

Sergey Valeryevich Shpirko

Course materials

Main literature:

1. Нестеров Ю.Е. Введение в выпуклую оптимизацию. М.: МЦНМО, 2010.

2. Nesterov Yu. Smooth minimization of non-smooth functions. // Mathematical Programming, 2005, v.103 (1), P.127-152. 

3. Nesterov Yu. Primal-dual subgradient methods for convex problems. // Mathematical programming, 2009, v.120 (1). 

4. Nesterov Yu. Gradient methods for minimizing composite functions. // Mathematical programming, vol. Online first (2012). 

5. Nesterov Yu. Efficiency of coordinate-descent methods on huge-scale optimization problems. // SIAM Journal on Optimization, V. 22, No.2, Р. 341-362 (2012).

6. Nesterov Yu. Subgradient methods for huge-scale optimization problems. // Mathematical programming, (May 2013).

Additional literature:
1.    Поляк Б.Т. Введение в оптимизацию. М.: МЦНМО, 1983.
2.    Nesterov Yu., Nemirovskii А. Interior point polynomial algorithms in convex programming. // SIAM: Philadelphia, 1994.
3.    Сухарев А.Г., Тимохов А.В., Федоров В.В. Курс методов оптимизации. М.: МЦНМО, 1986.
4.    Ben-Tal A., Nemirovski А. Lectures on Modern Convex Optimization. Analysis, Algorithms, and Engineering Applications. – SIAM: Philadelphia, 2001.
5.    Boyd S., Vandenberghe L. Convex Optimization. – United Kindom: Cambridge University Press, 2004.

Exam program

The exam will be held in the 1st semester

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