# 28917

## Автор(ов):

3

Параметры публикации

Доклад

## Название:

Application of the Mirror Descent Method to Minimize Average Loss Coming by a Poisson Flow

Да

## ISBN/ISSN:

978-3-9524269-2-0

## Наименование конференции:

• The 13th European Control Conference (ECC2014) (Strasbourg, France, 2014)

## Наименование источника:

• Proceedings of the 13th European Control Conference (ECC 2014, Strasbourg, France)

• Strasbourg

• EUCA

2014

## Страницы:

2194-2197
Аннотация
We treat a convex problem to minimize mean loss function for a stochastic system operating in continuous time. The losses on time horizon $T$ arise at the jump times of a Poisson process with intensity being an unknown random process. The oracle gives the randomly noised gradients of the loss function; the noises are additive, unbiased, with the bounded dual norm in mean square sense. The goal consists in minimizing the mean integral loss over a given convex compact set in $\mathbb{R}^N$. We propose a mirror descent algorithm and prove an explicit upper bound for the mean integral loss regret. The bound is of type $C\sqrt{T}$ with an explicit constant $C$. Finally, we describe an example of optimization for a server processing a stream of incoming requests, and we discuss simulation results.

## Библиографическая ссылка:

Назин А.В., Анулова С.В., Тремба А.А. Application of the Mirror Descent Method to Minimize Average Loss Coming by a Poisson Flow / Proceedings of the 13th European Control Conference (ECC 2014, Strasbourg, France). Strasbourg: EUCA, 2014. С. 2194-2197.