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ICML
2009
IEEE
14 years 9 months ago
Robot trajectory optimization using approximate inference
The general stochastic optimal control (SOC) problem in robotics scenarios is often too complex to be solved exactly and in near real time. A classical approximate solution is to ...
Marc Toussaint
DAGSTUHL
2007
13 years 10 months ago
Sampling-based Approximation Algorithms for Multi-stage Stochastic Optimization
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...
Chaitanya Swamy, David B. Shmoys
MOC
2000
76views more  MOC 2000»
13 years 8 months ago
Optimal approximation of stochastic differential equations by adaptive step-size control
We study the pathwise (strong) approximation of scalar stochastic differential equations with respect to the global error in the L2-norm. For equations with additive noise we estab...
Norbert Hofmann, Thomas Müller-Gronbach, Klau...
APPROX
2010
Springer
188views Algorithms» more  APPROX 2010»
13 years 10 months ago
Approximation Algorithms for Reliable Stochastic Combinatorial Optimization
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...
Evdokia Nikolova
TON
2010
151views more  TON 2010»
13 years 3 months ago
Throughput Optimal Distributed Power Control of Stochastic Wireless Networks
The Maximum Differential Backlog (MDB) control policy of Tassiulas and Ephremides has been shown to adaptively maximize the stable throughput of multihop wireless networks with ran...
Yufang Xi, Edmund M. Yeh