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ICPR
2008
IEEE
14 years 9 months ago
On refining dissimilarity matrices for an improved NN learning
Application-specific dissimilarity functions can be used for learning from a set of objects represented by pairwise dissimilarity matrices in this context. These dissimilarities m...
Elzbieta Pekalska, Robert P. W. Duin
SODA
1998
ACM
113views Algorithms» more  SODA 1998»
13 years 9 months ago
Fast Hierarchical Clustering and Other Applications of Dynamic Closest Pairs
We develop data structures for dynamic closest pair problems with arbitrary (not necessarily geometric) distance functions, based on a technique previously used by the author for ...
David Eppstein
WSCG
2004
185views more  WSCG 2004»
13 years 9 months ago
Automatic Fitting and Control of Complex Freeform Shapes in 3-D
In many computer graphics and computer-aided design problems, it is very common to find a smooth and well structured surface to fit a set of unstructured 3-dimensional data. Altho...
Yu Song, Joris S. M. Vergeest, Chensheng Wang
CEC
2009
IEEE
14 years 2 months ago
Differential Evolution with Laplace mutation operator
— Differential Evolution (DE) is a novel evolutionary approach capable of handling non-differentiable, non-linear and multi-modal objective functions. DE has been consistently ra...
Millie Pant, Radha Thangaraj, Ajith Abraham, Crina...
ICASSP
2011
IEEE
12 years 12 months ago
A kernelized maximal-figure-of-merit learning approach based on subspace distance minimization
We propose a kernelized maximal-figure-of-merit (MFoM) learning approach to efficiently training a nonlinear model using subspace distance minimization. In particular, a fixed,...
Byungki Byun, Chin-Hui Lee