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» Training a Support Vector Machine in the Primal
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ICPR
2008
IEEE
15 years 4 months ago
A fast revised simplex method for SVM training
Active set methods for training the Support Vector Machines (SVM) are advantageous since they enable incremental training and, as we show in this research, do not exhibit exponent...
Christopher Sentelle, Georgios C. Anagnostopoulos,...
ICML
2008
IEEE
15 years 10 months ago
Large scale manifold transduction
We show how the regularizer of Transductive Support Vector Machines (TSVM) can be trained by stochastic gradient descent for linear models and multi-layer architectures. The resul...
Michael Karlen, Jason Weston, Ayse Erkan, Ronan Co...
ICML
2003
IEEE
15 years 10 months ago
Transductive Learning via Spectral Graph Partitioning
We present a new method for transductive learning, which can be seen as a transductive version of the k nearest-neighbor classifier. Unlike for many other transductive learning me...
Thorsten Joachims
ISNN
2010
Springer
14 years 8 months ago
Pruning Training Samples Using a Supervised Clustering Algorithm
As practical pattern classification tasks are often very-large scale and serious imbalance such as patent classification, using traditional pattern classification techniques in ...
Minzhang Huang, Hai Zhao, Bao-Liang Lu
ANNPR
2008
Springer
14 years 12 months ago
Partial Discriminative Training of Neural Networks for Classification of Overlapping Classes
In applications such as character recognition, some classes are heavily overlapped but are not necessarily to be separated. For classification of such overlapping classes, either d...
Cheng-Lin Liu