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» Generalization Improvement in Multi-Objective Learning
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GECCO
2009
Springer
199views Optimization» more  GECCO 2009»
14 years 1 months ago
Using behavioral exploration objectives to solve deceptive problems in neuro-evolution
Encouraging exploration, typically by preserving the diversity within the population, is one of the most common method to improve the behavior of evolutionary algorithms with dece...
Jean-Baptiste Mouret, Stéphane Doncieux
CIKM
2007
Springer
14 years 21 days ago
A segment-based hidden markov model for real-setting pinyin-to-chinese conversion
Hidden markov model (HMM) is frequently used for Pinyin-toChinese conversion. But it only captures the dependency with the preceding character. Higher order markov models can brin...
Xiaohua Zhou, Xiaohua Hu, Xiaodan Zhang, Xiajiong ...
GECCO
2007
Springer
183views Optimization» more  GECCO 2007»
14 years 18 days ago
Evolving distributed agents for managing air traffic
Air traffic management offers an intriguing real world challenge to designing large scale distributed systems using evolutionary computation. The ability to evolve effective air t...
Adrian K. Agogino, Kagan Tumer
AI
2010
Springer
13 years 8 months ago
Understanding the scalability of Bayesian network inference using clique tree growth curves
Bayesian networks (BNs) are used to represent and ef ciently compute with multi-variate probability distributions in a wide range of disciplines. One of the main approaches to per...
Ole J. Mengshoel
BMCBI
2006
119views more  BMCBI 2006»
13 years 8 months ago
LS-NMF: A modified non-negative matrix factorization algorithm utilizing uncertainty estimates
Background: Non-negative matrix factorisation (NMF), a machine learning algorithm, has been applied to the analysis of microarray data. A key feature of NMF is the ability to iden...
Guoli Wang, Andrew V. Kossenkov, Michael F. Ochs