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COMPSAC
2004
IEEE
15 years 3 months ago
A Development Framework for Rapid Meta-Heuristics Hybridization
While meta-heuristics are effective for solving large-scale combinatorial optimization problems, they result from time-consuming trial-and-error algorithm design tailored to speci...
Hoong Chuin Lau, Wee Chong Wan, Min Kwang Lim, Ste...
ICCV
2007
IEEE
16 years 1 months ago
Boosting Invariance and Efficiency in Supervised Learning
In this paper we present a novel boosting algorithm for supervised learning that incorporates invariance to data transformations and has high generalization capabilities. While on...
Andrea Vedaldi, Paolo Favaro, Enrico Grisan
GECCO
2007
Springer
178views Optimization» more  GECCO 2007»
15 years 6 months ago
Transgenetic algorithm: a new evolutionary perspective for heuristics design
Transgenetic algorithms are evolutionary computing techniques based on living processes where cooperation is the main evolutionary strategy. Those processes contain the movement o...
Elizabeth Ferreira Gouvea Goldbarg, Marco Cé...
GECCO
2003
Springer
201views Optimization» more  GECCO 2003»
15 years 5 months ago
Solving Mastermind Using Genetic Algorithms
The MasterMind game involves decoding a secret code. The classic game is a code of six possible colors in four slots. The game has been analyzed and optimal strategies have been po...
Tom Kalisker, Doug Camens
GIS
2005
ACM
16 years 23 days ago
Two ellipse-based pruning methods for group nearest neighbor queries
Group nearest neighbor (GNN) queries are a relatively new type of operations in spatial database applications. Different from a traditional kNN query which specifies a single quer...
Hongga Li, Hua Lu, Bo Huang, Zhiyong Huang