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GECCO
2006
Springer
170views Optimization» more  GECCO 2006»
15 years 1 months ago
How an optimal observer can collapse the search space
Many metaheuristics have difficulty exploring their search space comprehensively. Exploration time and efficiency are highly dependent on the size and the ruggedness of the search...
Christophe Philemotte, Hugues Bersini
BMCBI
2008
178views more  BMCBI 2008»
14 years 10 months ago
A discriminative method for protein remote homology detection and fold recognition combining Top-n-grams and latent semantic ana
Background: Protein remote homology detection and fold recognition are central problems in bioinformatics. Currently, discriminative methods based on support vector machine (SVM) ...
Bin Liu, Xiaolong Wang, Lei Lin, Qiwen Dong, Xuan ...
COR
2008
122views more  COR 2008»
14 years 10 months ago
First steps to the runtime complexity analysis of ant colony optimization
: The paper presents results on the runtime complexity of two ant colony optimization (ACO) algorithms: Ant System, the oldest ACO variant, and GBAS, the first ACO variant for whic...
Walter J. Gutjahr
EC
2010
157views ECommerce» more  EC 2010»
14 years 10 months ago
Memetic Algorithms for Continuous Optimisation Based on Local Search Chains
Memetic algorithms with continuous local search methods have arisen as effective tools to address the difficulty of obtaining reliable solutions of high precision for complex cont...
Daniel Molina, Manuel Lozano, Carlos García...
JACM
2006
99views more  JACM 2006»
14 years 9 months ago
Finding a maximum likelihood tree is hard
Abstract. Maximum likelihood (ML) is an increasingly popular optimality criterion for selecting evolutionary trees [Felsenstein 1981]. Finding optimal ML trees appears to be a very...
Benny Chor, Tamir Tuller