AAAI
2012
12 years 5 months ago
2012
We address the problem of spatial conservation planning in which the goal is to maximize the expected spread of cascades of an endangered species by strategically purchasing land ...
AAAI
2011
13 years 3 months ago
2011
Sustainable resource management in many domains presents large continuous stochastic optimization problems, which can often be modeled as Markov decision processes (MDPs). To solv...
ICASSP
2011
IEEE
13 years 6 months ago
2011
IEEE
Stochastic optimization arising from precoding in a multi-antenna fading channel with channel mean feedback to maximize data rates is important but challenging. The use of relayin...
AOR
2010
14 years 14 days ago
2010
We show how a technique from signal processing known as zero-delay convolution can be used to develop more efficient dynamic programming algorithms for a broad class of stochastic...
ANOR
2010
14 years 1 months ago
2010
This paper considers online stochastic optimization problems where uncertainties are characterized by a distribution that can be sampled and where time constraints severely limit t...
MOR
2007
14 years 2 months ago
2007
Real-world networks often need to be designed under uncertainty, with only partial information and predictions of demand available at the outset of the design process. The field ...
DAGSTUHL
2007
14 years 4 months ago
2007
Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizatio...
WSC
2008
14 years 5 months ago
2008
We consider discrete stochastic optimization problems where the objective function can only be estimated by a simulation oracle; the oracle is defined only at the discrete points....
FOCS
2004
IEEE
14 years 6 months ago
2004
IEEE
Stochastic optimization problems attempt to model uncertainty in the data by assuming that (part of) the input is specified in terms of a probability distribution. We consider the...
ISCIS
2003
Springer
14 years 8 months ago
2003
Springer
In this paper, we study an adaptive random search method based on continuous action-set learning automaton for solving stochastic optimization problems in which only the noisecorr...