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NECO
2008
112views more  NECO 2008»
15 years 3 months ago
Second-Order SMO Improves SVM Online and Active Learning
Iterative learning algorithms that approximate the solution of support vector machines (SVMs) have two potential advantages. First, they allow for online and active learning. Seco...
Tobias Glasmachers, Christian Igel
127
Voted
ITICSE
1997
ACM
15 years 8 months ago
A genetic algorithms tutorial tool for numerical function optimisation
The field of Genetic Algorithms has grown into a huge area over the last few years. Genetic Algorithms are adaptive methods, which can be used to solve search and optimisation pro...
Edmund K. Burke, D. B. Varley
158
Voted
ANNPR
2006
Springer
15 years 7 months ago
Visual Classification of Images by Learning Geometric Appearances Through Boosting
We present a multiclass classification system for gray value images through boosting. The feature selection is done using the LPBoost algorithm which selects suitable features of a...
Martin Antenreiter, Christian Savu-Krohn, Peter Au...
TCS
2010
15 years 2 months ago
Active learning in heteroscedastic noise
We consider the problem of actively learning the mean values of distributions associated with a finite number of options. The decision maker can select which option to generate t...
András Antos, Varun Grover, Csaba Szepesv&a...
TNN
2008
181views more  TNN 2008»
15 years 3 months ago
Optimized Approximation Algorithm in Neural Networks Without Overfitting
In this paper, an optimized approximation algorithm (OAA) is proposed to address the overfitting problem in function approximation using neural networks (NNs). The optimized approx...
Yinyin Liu, Janusz A. Starzyk, Zhen Zhu