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GECCO
2007
Springer
558views Optimization» more  GECCO 2007»
16 years 28 days ago
A chain-model genetic algorithm for Bayesian network structure learning
Bayesian Networks are today used in various fields and domains due to their inherent ability to deal with uncertainty. Learning Bayesian Networks, however is an NP-Hard task [7]....
Ratiba Kabli, Frank Herrmann, John McCall
ISCI
2008
95views more  ISCI 2008»
15 years 6 months ago
Modified constrained learning algorithms incorporating additional functional constraints into neural networks
In this paper, two modified constrained learning algorithms are proposed to obtain better generalization performance and faster convergence rate. The additional cost terms of the ...
Fei Han, Qing-Hua Ling, De-Shuang Huang
AAAI
2007
15 years 9 months ago
A Reinforcement Learning Algorithm with Polynomial Interaction Complexity for Only-Costly-Observable MDPs
An Unobservable MDP (UMDP) is a POMDP in which there are no observations. An Only-Costly-Observable MDP (OCOMDP) is a POMDP which extends an UMDP by allowing a particular costly a...
Roy Fox, Moshe Tennenholtz
AIME
2005
Springer
15 years 8 months ago
An Algorithm to Learn Causal Relations Between Genes from Steady State Data: Simulation and Its Application to Melanoma Dataset
In recent years, a few researchers have challenged past dogma and suggested methods (such as the IC algorithm) for inferring causal relationship among variables using steady state ...
Xin Zhang, Chitta Baral, Seungchan Kim
EGC
2005
Springer
16 years 6 days ago
Learning Automata Based Algorithms for Mapping of a Class of Independent Tasks over Highly Heterogeneous Grids
Computational grid provides a platform for exploiting various computational resources over wide area networks. One of the concerns in implementing computational grid environment is...
S. Ghanbari, Mohammad Reza Meybodi