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CDC
2009
IEEE
156views Control Systems» more  CDC 2009»
13 years 11 months ago
An optimization approach to adaptive Kalman filtering
— In this paper, an optimization-based adaptive Kalman filtering method is proposed. The method produces an estimate of the process noise covariance matrix Q by solving an optim...
Maja Karasalo, Xiaoming Hu
GECCO
2003
Springer
14 years 29 days ago
A Case for Codons in Evolutionary Algorithms
A new method is developed for representation and encoding in population-based evolutionary algorithms. The method is inspired by the biological genetic code and utilizes a many-to-...
Joshua Gilbert, Margaret J. Eppstein
CSDA
2007
100views more  CSDA 2007»
13 years 7 months ago
Estimation in a linear multivariate measurement error model with a change point in the data
A linear multivariate measurement error model AX = B is considered. The errors in A B are row-wise finite dependent, and within each row, the errors may be correlated. Some of th...
Alexander Kukush, Ivan Markovsky, Sabine Van Huffe...
PE
2008
Springer
106views Optimization» more  PE 2008»
13 years 7 months ago
Heavy traffic analysis of polling models by mean value analysis
In this paper we present a new approach to derive heavy-traffic asymptotics for polling models. We consider the classical cyclic polling model with exhaustive or gated service at ...
Robert D. van der Mei, Erik M. M. Winands
GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
13 years 5 months ago
Uncertainty handling CMA-ES for reinforcement learning
The covariance matrix adaptation evolution strategy (CMAES) has proven to be a powerful method for reinforcement learning (RL). Recently, the CMA-ES has been augmented with an ada...
Verena Heidrich-Meisner, Christian Igel