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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
IJCNN
2006
IEEE
14 years 3 months ago
Sparse Optimization for Second Order Kernel Methods
— We present a new optimization procedure which is particularly suited for the solution of second-order kernel methods like e.g. Kernel-PCA. Common to these methods is that there...
Roland Vollgraf, Klaus Obermayer
GLOBECOM
2009
IEEE
14 years 27 days ago
Exploring Simulated Annealing and Graphical Models for Optimization in Cognitive Wireless Networks
In this paper we discuss the design of optimization algorithms for cognitive wireless networks (CWNs). Maximizing the perceived network performance towards applications by selectin...
Elena Meshkova, Janne Riihijärvi, Andreas Ach...
WSC
2000
13 years 10 months ago
Low cost response surface methods for and from simulation optimization
We propose "low cost response surface methods" (LCRSM) that typically require half the experimental runs of standard response surface methods based on central composite ...
Theodore Allen, Liyang Yu
ESA
2008
Springer
136views Algorithms» more  ESA 2008»
13 years 10 months ago
Oblivious Randomized Direct Search for Real-Parameter Optimization
The focus is on black-box optimization of a function f : RN R given as a black box, i. e. an oracle for f-evaluations. This is commonly called direct search, and in fact, most meth...
Jens Jägersküpper