6016

Автор(ы): 

Автор(ов): 

2

Параметры публикации

Тип публикации: 

Доклад

Название: 

Randomized Methods Based on New Monte Carlo Schemes for Convex Optimization

Наименование конференции: 

  • EURO Mini-Conference “Continuous Optimization and knowledge-Based Technologies” (EurOPT’2008)

Город: 

  • -

Издательство: 

  • -

Год издания: 

2008

Страницы: 

-
Аннотация
We address randomized methods for convex optimization based on generating points uniformly distributed in a convex set. We estimate the rate of convergence for such methods and demonstrate the link with the center of gravity method. To implement such approach we exploit two modern Monte Carlo schemes for generating points which are approximately uniformly distributed in a given convex set. Both methods use boundary oracle to find an intersection of a ray and the set. The first method is Hit-and-Run, the second is sometimes called Shake-and-Bake. Numerical simulation results look very promising.

Библиографическая ссылка: 

Поляк Б.Т., Грязина Е.Н. Randomized Methods Based on New Monte Carlo Schemes for Convex Optimization / . -: -, 2008. С. -.