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LASVM is an approximate SVM solver that uses online approximation. It reaches accuracies similar to that of a real SVM after performing a single sequential pass through the training examples. Further benefits can be achieved using selective sampling techniques to choose which example should be considered next. As show in the graph, LASVM requires considerably less memory than a regular SVM solver. This becomes a considerable speed advantage for large training sets. In fact LASVM has been used to train a 10 class SVM classifier with 8 million examples on a single processor.

Online videos of talks or lectures about Machine Learning related topics

The Journal of Machine Learning Research (JMLR) provides an international forum for the electronic and paper publication of high-quality scholarly articles in all areas of machine learning. All published papers are freely available online.