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GECCO
2006
Springer
168views Optimization» more  GECCO 2006»
13 years 11 months ago
A Bayesian approach to learning classifier systems in uncertain environments
In this paper we propose a Bayesian framework for XCS [9], called BXCS. Following [4], we use probability distributions to represent the uncertainty over the classifier estimates ...
Davide Aliprandi, Alex Mancastroppa, Matteo Matteu...
TWC
2008
127views more  TWC 2008»
13 years 7 months ago
Energy-Delay Analysis of MAC Protocols in Wireless Networks
In this paper the tradeoff between energy and delay for wireless networks is studied. A network using a request-to-send (RTS) and clear-to-send (CTS) type medium access control (M...
Shih Yu Chang, Wayne E. Stark, Achilleas Anastasop...
TEC
2010
112views more  TEC 2010»
13 years 2 months ago
Population-Based Algorithm Portfolios for Numerical Optimization
In this paper, we consider the scenario that a population-based algorithm is applied to a numerical optimization problem and a solution needs to be presented within a given time bu...
Fei Peng, Ke Tang, Guoliang Chen, Xin Yao
GECCO
2000
Springer
138views Optimization» more  GECCO 2000»
13 years 11 months ago
Time Complexity of genetic algorithms on exponentially scaled problems
This paper gives a theoretical and empirical analysis of the time complexity of genetic algorithms (GAs) on problems with exponentially scaled building blocks. It is important to ...
Fernando G. Lobo, David E. Goldberg, Martin Pelika...
NIPS
1998
13 years 9 months ago
SMEM Algorithm for Mixture Models
When learning a mixture model, we suffer from the local optima and model structure determination problems. In this paper, we present a method for simultaneously solving these prob...
Naonori Ueda, Ryohei Nakano, Zoubin Ghahramani, Ge...