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151
Voted
GECCO
2008
Springer
177views Optimization» more  GECCO 2008»
15 years 4 months ago
Reduced computation for evolutionary optimization in noisy environment
Evolutionary Algorithms’ (EAs’) application to real world optimization problems often involves expensive fitness function evaluation. Naturally this has a crippling effect on ...
Maumita Bhattacharya
132
Voted
NIPS
2000
15 years 5 months ago
A Support Vector Method for Clustering
We present a novel method for clustering using the support vector machine approach. Data points are mapped to a high dimensional feature space, where support vectors are used to d...
Asa Ben-Hur, David Horn, Hava T. Siegelmann, Vladi...
140
Voted
ICIP
2009
IEEE
15 years 1 months ago
Efficient reduction of support vectors in kernel-based methods
Kernel-based methods, e.g., support vector machine (SVM), produce high classification performances. However, the computation becomes time-consuming as the number of the vectors su...
Takumi Kobayashi, Nobuyuki Otsu
160
Voted
ISCI
2008
165views more  ISCI 2008»
15 years 3 months ago
Support vector regression from simulation data and few experimental samples
This paper considers nonlinear modeling based on a limited amount of experimental data and a simulator built from prior knowledge. The problem of how to best incorporate the data ...
Gérard Bloch, Fabien Lauer, Guillaume Colin...
SCHOLARPEDIA
2008
89views more  SCHOLARPEDIA 2008»
15 years 2 months ago
Support vector clustering
We present a novel method for clustering using the support vector machine approach. Data points are mapped to a high dimensional feature space, where support vectors are used to d...
Asa Ben-Hur