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» Objective improvement in information-geometric optimization
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GECCO
2009
Springer
126views Optimization» more  GECCO 2009»
15 years 2 months ago
Improving NSGA-II with an adaptive mutation operator
The performance of a Multiobjective Evolutionary Algorithm (MOEA) is crucially dependent on the parameter setting of the operators. The most desired control of such parameters pre...
Arthur Gonçalves Carvalho, Aluizio F. R. Ar...
AAAI
2012
13 years 8 hour ago
Transfer Learning with Graph Co-Regularization
Transfer learning proves to be effective for leveraging labeled data in the source domain to build an accurate classifier in the target domain. The basic assumption behind transf...
Mingsheng Long, Jianmin Wang 0001, Guiguang Ding, ...
GECCO
2009
Springer
148views Optimization» more  GECCO 2009»
15 years 26 days ago
Tracking multiple objects in non-stationary video
One of the key problems in computer vision and pattern recognition is tracking. Multiple objects, occlusion, and tracking moving objects using a moving camera are some of the chal...
Hoang Nguyen, Bir Bhanu
80
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GECCO
1999
Springer
126views Optimization» more  GECCO 1999»
15 years 1 months ago
Improving Genetic Algorithms by Search Space Reductions (with Applications to Flow Shop Scheduling)
Crossover operators that preserve common components can also preserve representation level constraints. Consequently, these constraints can be used to beneficially reduce the sea...
Stephen Y. Chen, Stephen F. Smith
GIS
2004
ACM
15 years 10 months ago
A novel improvement to the R*-tree spatial index using gain/loss metrics
The R*-tree is a state-of-the-art spatial index structure. It has already found its way into commercial systems. The most important improvement of the R*-tree over the original R-...
Donghui Zhang, Tian Xia