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SIAMJO
2002
124views more  SIAMJO 2002»
13 years 5 months ago
The Sample Average Approximation Method for Stochastic Discrete Optimization
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...
Anton J. Kleywegt, Alexander Shapiro, Tito Homem-d...
SODA
2012
ACM
240views Algorithms» more  SODA 2012»
11 years 8 months ago
Simultaneous approximations for adversarial and stochastic online budgeted allocation
Motivated by online ad allocation, we study the problem of simultaneous approximations for the adversarial and stochastic online budgeted allocation problem. This problem consists...
Vahab S. Mirrokni, Shayan Oveis Gharan, Morteza Za...
DATE
2007
IEEE
92views Hardware» more  DATE 2007»
14 years 17 days ago
Random sampling of moment graph: a stochastic Krylov-reduction algorithm
In this paper we introduce a new algorithm for model order reduction in the presence of parameter or process variation. Our analysis is performed using a graph interpretation of t...
Zhenhai Zhu, Joel R. Phillips
ICIP
2003
IEEE
14 years 7 months ago
Algorithms for stochastic approximations of curvature flows
Curvature flows have been extensively considered from a deterministic point of view. They have been shown to be useful for a number of applications including crystal growth, flame...
Gozde B. Unal, Delphine Nain, G. Ben-Arous, Nahum ...
FSTTCS
2006
Springer
13 years 10 months ago
Approximation Algorithms for 2-Stage Stochastic Optimization Problems
Abstract. Stochastic optimization is a leading approach to model optimization problems in which there is uncertainty in the input data, whether from measurement noise or an inabili...
Chaitanya Swamy, David B. Shmoys