509 search results - page 9 / 102 » Using Learning for Approximation in Stochastic Processes |
SAGA
2009
Springer
14 years 1 months ago
2009
Springer
We propose a generic method for obtaining quickly good upper bounds on the minimal value of a multistage stochastic program. The method is based on the simulation of a feasible dec...
DAGSTUHL
2004
13 years 8 months ago
2004
We study algorithms for approximation of the mild solution of stochastic heat equations on the spatial domain ]0, 1[ d . The error of an algorithm is defined in L2-sense. We derive...
NN
2006
Springer
13 years 7 months ago
2006
Springer
The way of propagating and control of stochastic signals through Universal Learning Networks (ULNs) and its applications are proposed. ULNs have been already developed to form a s...
SIAMCO
2002
13 years 7 months ago
2002
There is a large literature on the rate of convergence problem for general unconstrained stochastic approximations. Typically, one centers the iterate n about the limit point then...
SODA
2012
ACM
11 years 9 months ago
2012
ACM
In the Stochastic Orienteering problem, we are given a metric, where each node also has a job located there with some deterministic reward and a random size. (Think of the jobs as...