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» Optimization by Simulation Metamodelling Methods
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CORR
2008
Springer
133views Education» more  CORR 2008»
13 years 9 months ago
Estimating divergence functionals and the likelihood ratio by convex risk minimization
We develop and analyze M-estimation methods for divergence functionals and the likelihood ratios of two probability distributions. Our method is based on a non-asymptotic variatio...
XuanLong Nguyen, Martin J. Wainwright, Michael I. ...
IDA
2008
Springer
13 years 9 months ago
A comprehensive analysis of hyper-heuristics
Meta-heuristics such as simulated annealing, genetic algorithms and tabu search have been successfully applied to many difficult optimization problems for which no satisfactory pro...
Ender Özcan, Burak Bilgin, Emin Erkan Korkmaz
JMLR
2006
105views more  JMLR 2006»
13 years 9 months ago
Linear State-Space Models for Blind Source Separation
We apply a type of generative modelling to the problem of blind source separation in which prior knowledge about the latent source signals, such as time-varying auto-correlation a...
Rasmus Kongsgaard Olsson, Lars Kai Hansen
WSC
2001
13 years 10 months ago
Stochastic modeling of airlift operations
Large-scale military deployments require transporting equipment and personnel over long distances in a short time. Planning an efficient airlift system is complicated and several ...
Julien Granger, Ananth Krishnamurthy, Stephen M. R...
EC
2012
289views ECommerce» more  EC 2012»
12 years 4 months ago
Multimodal Optimization Using a Bi-Objective Evolutionary Algorithm
In a multimodal optimization task, the main purpose is to find multiple optimal solutions (global and local), so that the user can have a better knowledge about different optima...
Kalyanmoy Deb, Amit Saha