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» Newton's method and its use in optimization
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CVPR
2008
IEEE
14 years 9 months ago
In defense of Nearest-Neighbor based image classification
State-of-the-art image classification methods require an intensive learning/training stage (using SVM, Boosting, etc.) In contrast, non-parametric Nearest-Neighbor (NN) based imag...
Oren Boiman, Eli Shechtman, Michal Irani
GECCO
2003
Springer
137views Optimization» more  GECCO 2003»
14 years 23 days ago
The Spatially-Dispersed Genetic Algorithm
Abstract. Spatially structured population models improve the performance of genetic algorithms by assisting the selection scheme in maintaining diversity. A significant concern wi...
Grant Dick
TNN
1998
114views more  TNN 1998»
13 years 7 months ago
Bayesian retrieval in associative memories with storage errors
Abstract—It is well known that for finite-sized networks, onestep retrieval in the autoassociative Willshaw net is a suboptimal way to extract the information stored in the syna...
Friedrich T. Sommer, Peter Dayan
SMA
2009
ACM
223views Solid Modeling» more  SMA 2009»
14 years 2 months ago
Particle-based forecast mechanism for continuous collision detection in deformable environments
Collision detection in geometrically complex scenes is crucial in physical simulations and real time applications. Works based on spatial hierarchical structures have been propose...
Thomas Jund, David Cazier, Jean-François Du...
GECCO
2007
Springer
194views Optimization» more  GECCO 2007»
14 years 1 months ago
Hybrid coevolutionary algorithms vs. SVM algorithms
As a learning method support vector machine is regarded as one of the best classifiers with a strong mathematical foundation. On the other hand, evolutionary computational techniq...
Rui Li, Bir Bhanu, Krzysztof Krawiec