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SIAMJO
2002
13 years 7 months ago
2002
In this paper we study a Monte Carlo simulation based approach to stochastic discrete optimization problems. The basic idea of such methods is that a random sample is generated and...
MP
2010
13 years 6 months ago
2010
Convex optimization problems arising in applications, possibly as approximations of intractable problems, are often structured and large scale. When the data are noisy, it is of i...
DAGSTUHL
2007
13 years 9 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...
IR
2010
13 years 6 months ago
2010
Recently direct optimization of information retrieval (IR) measures becomes a new trend in learning to rank. Several methods have been proposed and the effectiveness of them has ...
APPROX
2010
Springer
13 years 9 months ago
2010
Springer
We consider optimization problems that can be formulated as minimizing the cost of a feasible solution wT x over an arbitrary combinatorial feasible set F {0, 1}n . For these pro...